Image processing circuit, and display panel driver and display device mounting the circuit

ABSTRACT

A display panel driver includes: a compression circuit, when receiving image data of N×M pixels of a target block, generating compressed image data corresponding to the target block by compressing the image data; an image memory storing the compressed image data; a decompression circuit generating decompressed image data by decompressing the compressed image data from the image memory; and a drive circuit driving a display panel in response to the decompressed image data. The compression circuit selects one of a plurality of compression methods based on a correlation between the image data of the N×M pixels, and generates the compressed image data by the selected compression method. The plurality of compression methods includes: a first method calculating a first value corresponding to image data of the N×M pixels and putting the first value in the compressed image data, a second method calculating a second value corresponding to image data of n pixels of the N×M pixels and putting the second value in the compressed image data, and a third method calculating a bit plane reducing data by performing a bit plane reduction process independently on image data of each of the N×M pixels and putting the bit plane reducing data in the compressed image data.

INCORPORATED BY REFERENCE

This application is based upon and claims the benefit of priority fromJapanese patent application No. 2008-171364 filed on Jun. 30, 2008, thedisclosure of which is incorporated herein in its entirety by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to an image processing circuit, and adisplay panel driver and display device mounting the image processingcircuit.

2. Description of Related Art

In a mobile apparatus such as a mobile phone and a PDA (Personal DigitalAssistant), an LCD (Liquid Crystal Display) panel or another displaypanel is generally mounted. Since the mobile apparatus relies on abattery for a power supply, it is important to reduce power consumptionof a display panel and a display panel driver for driving the displaypanel (for example, an LCD driver), resulting in extension of anoperating time.

One method for reducing power consumption is to mount an image memory onthe display panel driver and reduce the frequency of access to the imagememory. For example, if image data is written to the image memory onlyin a case where an image is changed, an electric power required fortransfer of image data is reduced and accordingly the power consumptioncan be reduced.

One problem about the mounting of the image memory on the display paneldriver is increase in a required memory capacity. In these years,resolution and the number of gradations of the display panel areincreasing because of diversification of contents to be displayed. Forthis reason, increase in a capacity of the image memory is demanded.However, since leading to increase in a cost, the increase in thecapacity of the image memory is not favorable.

One method for reducing the memory capacity is to compress image dataand store the compressed data in the image memory. Various types ofcompression methods of image data stored in the image memory areproposed.

One commonly-known compression method is block coding for performing acompression process in units of blocks including a plurality of pixels.In the block coding, image data of a plurality of pixels constitutingthe block is represented by at least one representative value. Forexample, Japanese Laid-Open Patent Application JP-P 2007-312126A(US2007269118 (A1)) discloses a compression method for representingimage dada of pixels in a block by a plurality of representative value.In the compression method described in this publication, one ofthree-level BTC (Block Truncation Coding) and two-level BTC is selecteddepending on image data, and compression of the image data is performedby the selected coding technique. Specifically, RG_(B) data is convertedinto YUV data, and the three-level BTC is employed in a case where adifference in brightness data of pixels and a difference of colordifference data are large in each block. In a case where the differencesare not so large, the two-level BTC is employed. In addition, JapaneseLaid-Open Patent Application JP-A-Heisei 10-66072 discloses acompression method for constituting compressed image data by using anaverage value, a deviation, and a piece of bit plane information ofimage data in pixels of a block.

One problem of the block coding is block noise caused by a difference ofcorrelation between adjacent blocks. For example, when a compressionprocess is performed in units of blocks each including 4 pixels, a casewill be considered in which: a correlation of image data among 4 pixelsin a certain block is high; and a correlation of image data among 4pixels in an adjacent block is low. In this case, a large error existsin the block with low correlation, and the block with a large error isarranged next to the block with a small error. Human eyes will recognizethis as block noise.

Another commonly-known compression method is a method for independentlyprocessing image data of each pixel such as the dither processing usinga dither matrix. Such compression method is disclosed in, for example,Japanese Laid-Open Patent Application JP-P 2003-162272A (U.S. Pat. No.7,483,574 (B2)). In the compression method for independently processingimage data of each pixel, block noise is not generated. However, in thecompression method for independently processing image data of eachpixel, there is a problem that generates granular noise in an image inwhich pixels with high correlation of image data are arranged.

Japanese Laid-Open Patent Application JP-P 2006-311474A (US2006220984(A1)) discloses a technique that: uses the block coding for an imagewith moderate gradation; and independently processes image data of eachpixel when gradations of adjacent pixels are widely different from eachother. This publication describes that the two functions are necessaryto perform the image processing for any images without collapse.

However, the inventors have now discovered the following facts.According to study by the inventors, the compression method disclosed inJapanese Laid-Open Patent Application JP-P 2006-311474A does notsubstantially reduce granular noise. When even one pixel having lowcorrelation of image data to other pixels exists in pixels included in ablock, the technique disclosed in Japanese Laid-Open Patent ApplicationJP-P 2006-311474A employs a compression method for independentlyprocessing image data of each pixel. For example, in a case where theblock includes pixels arranged in 2 rows by 2 columns, even when acorrelation of image data between two pixels is high and a correlationof image data of remaining two pixels with the former two pixels is low,a compression method for independently processing image data of eachpixel is employed. In this case, the compression method forindependently processing image data of each pixel is employed for thepixel with a high correlation of image data, resulting in generation ofgranular noise.

SUMMARY

The present invention seeks to solve one or more of the above problems,or to improve upon those problems at least in part.

In one embodiment, a display panel driver includes: a compressioncircuit configured to, when receiving image data of N×M (N and M isinteger, N×M≧4) pixels of a target block, generate compressed image datacorresponding to the target block by compressing the image data; animage memory configured to store the compressed image data; adecompression circuit configured to generate decompressed image data bydecompressing the compressed image data reading from the image memory;and a drive circuit configured to drive a display panel in response tothe decompressed image data. The compression circuit selects one of aplurality of compression methods based on a correlation between theimage data of the N×M pixels of the target block, and generates thecompressed image data by using the selected compression method. Theplurality of compression methods includes: a first compression methodwhich calculates a first representative value corresponding to imagedata of the N×M pixels and puts the first representative value in thecompressed image data, a second compression method which calculates asecond representative value corresponding to image data of n (2≦n<N×M)pixels of the N×M pixels and puts the second representative value in thecompressed image data, and a third compression method which calculates afirst bit plane reducing data by performing a bit plane reductionprocess independently on image data of each of the N×M pixels and putsthe first bit plane reducing data in the compressed image data.

In another embodiment, a display device includes: a display panel; and adisplay panel driver configured to drive the display panel. The displaypanel driver includes: a compression circuit configured to, whenreceiving image data of N×M (N and M is integer, N×M≧4) pixels of atarget block, generate compressed image data corresponding to the targetblock by compressing the image data, an image memory configured to storethe compressed image data, a decompression circuit configured togenerate decompressed image data by decompressing the compressed imagedata reading from the image memory, and a drive circuit configured todrive a display panel in response to the decompressed image data. Thecompression circuit selects one of a plurality of compression methodsbased on a correlation between the image data of the N×M pixels of thetarget block, and generates the compressed image data by using theselected compression method. The plurality of compression methodsincludes: a first compression method which calculates a firstrepresentative value corresponding to image data of the N×M pixels andputs the first representative value in the compressed image data, asecond compression method which calculates a second representative valuecorresponding to image data of n (2≦n<N×M) pixels of the N×M pixels andputs the second representative value in the compressed image data, and athird compression method which calculates a first bit plane reducingdata by performing a bit plane reduction process independently on imagedata of each of the N×M pixels and puts the first bit plane reducingdata in the compressed image data.

In another embodiment, an image processing circuit includes: acompression circuit configured to, when receiving image data of N×M (Nand M is integer, N×M≧4) pixels of a target block, generate compressedimage data corresponding to the target block by compressing the imagedata. The compression circuit selects one of a plurality of compressionmethods based on a correlation between the image data of the N×M pixelsof the target block, and generates the compressed image data by usingthe selected compression method. The plurality of compression methodsincludes: a first compression method which calculates a firstrepresentative value corresponding to image data of the N×M pixels andputs the first representative value in the compressed image data, asecond compression method which calculates a second representative valuecorresponding to image data of n (2≦n<N×M) pixels of the N×M pixels andputs the second representative value in the compressed image data, and athird compression method which calculates a first bit plane reducingdata by performing a bit plane reduction process independently on imagedata of each of the N×M pixels and puts the first bit plane reducingdata in the compressed image data.

In another embodiment, a display panel driver includes: a compressioncircuit configured to, when receiving image data of a plurality ofpixels of a target block, generate compressed image data correspondingto the target block by compressing the image data; an image memoryconfigured to store the compressed image data; a decompression circuitconfigured to generate decompressed image data by decompressing thecompressed image data reading from the image memory; and a drive circuitconfigured to drive a display panel in response to the decompressedimage data. The compression circuit selects one of a plurality ofcompression methods based on a correlation between the image data of theplurality of pixels of the target block, and generates the compressedimage data by using the selected compression method. The number of bitsof the compressed image data is constant regardless of the plurality ofcompression method. The compressed image data includes a compressiontype recognition bit indicating a type of the selected compressionmethod. The number of bits of the compression type recognition bit ofthe compressed image data becomes low, when the correlation between theimage data of the plurality of pixels becomes high.

In another embodiment, a display device includes: a display panel; and adisplay panel driver configured to drive the display panel. The displaypanel driver includes: a compression circuit configured to, whenreceiving image data of a plurality of pixels of a target block,generate compressed image data corresponding to the target block bycompressing the image data, an image memory configured to store thecompressed image data, a decompression circuit configured to generatedecompressed image data by decompressing the compressed image datareading from the image memory, and a drive circuit configured to drive adisplay panel in response to the decompressed image data. Thecompression circuit selects one of a plurality of compression methodsbased on a correlation between the image data of the plurality of pixelsof the target block, and generates the compressed image data by usingthe selected compression method. The number of bits of the compressedimage data is constant regardless of the plurality of compressionmethod. The compressed image data includes a compression typerecognition bit indicating a type of the selected compression method.The number of bits of the compression type recognition bit of thecompressed image data becomes low, when the correlation between theimage data of the plurality of pixels becomes high.

In another embodiment, an image processing circuit includes: acompression circuit configured to, when receiving image data of aplurality of pixels of a target block, generate compressed image datacorresponding to the target block by compressing the image data. Thecompression circuit selects one of a plurality of compression methodsbased on a correlation between the image data of the plurality of pixelsof the target block, and generates the compressed image data by usingthe selected compression method. The number of bits of the compressedimage data is constant regardless of the plurality of compressionmethod. The compressed image data includes a compression typerecognition bit indicating a type of the selected compression method.The number of bits of the compression type recognition bit of thecompressed image data becomes low, when the correlation between theimage data of the plurality of pixels becomes high.

According to the present invention, an image compression that reducesblock noise and granular noise can be performed.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other objects, advantages and features of the presentinvention will be more apparent from the following description ofcertain preferred embodiments taken in conjunction with the accompanyingdrawings, in which:

FIG. 1 is a block diagram showing a configuration of a liquid crystaldisplay device according to a first embodiment of the present invention;

FIG. 2 is a conceptual diagram showing an operation of a line memory;

FIG. 3 is a view showing arrangement of pixels of a target block;

FIGS. 4A to 4D are conceptual diagrams showing correlations of imagedata of pixels in the target block;

FIG. 5 is a flowchart showing a procedure of judgment of correlations ofimage data in the first embodiment;

FIG. 6A is a conceptual view to explain (1×4) image compression;

FIG. 6B is a conceptual view to explain a decompression method forcompressed image data compressed by the (1×4) image compression;

FIG. 7 is a view showing a format of (1×4) compressed data;

FIG. 8A is a conceptual view to explain (2+1×2) image compression;

FIG. 8B is a conceptual view to explain a decompression method forcompressed image data compressed by the (2+1×2) image compression;

FIG. 9A is a view showing a format of (2+1×2) compressed data;

FIG. 9B is a view showing a format of (2+1×2) compressed data;

FIG. 10A is a conceptual view to explain (2×2) image compression;

FIG. 10B is a conceptual view to explain a decompression method forcompressed image data compressed by the (2×2) image compression;

FIG. 11A is a view showing a format of (2×2) compressed data;

FIG. 11B is a view showing the format of (2×2) compressed data;

FIG. 12A is a conceptual view to explain (4×1) image compression;

FIG. 12B is a conceptual view to explain a decompression method forcompressed image data compressed by the (4×1) image compression;

FIG. 13 is a view showing a format of (4×1) compressed data;

FIG. 14 is a view showing an example of a basic matrix used forgenerating error data a;

FIG. 15 is a block diagram showing a configuration of a liquid crystaldisplay device according to a second embodiment of the presentinvention;

FIG. 16 is a flowchart showing an operation of the liquid crystaldisplay device according to the second embodiment of the presentinvention;

FIG. 17A is a view showing an example of a particular pattern to which alossless compression is performed;

FIG. 17B is a view showing another example of the particular pattern towhich the lossless compression is performed;

FIG. 17C is a view showing another example of the particular pattern towhich the lossless compression is performed;

FIG. 17D is a view showing another example of the particular pattern towhich the lossless compression is performed;

FIG. 17E is a view showing another example of the particular pattern towhich the lossless compression is performed;

FIG. 17F is a view showing another example of the particular pattern towhich the lossless compression is performed;

FIG. 17G is a view showing another example of the particular pattern towhich the lossless compression is performed;

FIG. 17H is a view showing another example of the particular pattern towhich the lossless compression is performed; and

FIG. 18 is a view showing a format of lossless compression data.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The invention will be now described herein with reference toillustrative embodiments. Those skilled in the art will recognize thatmany alternative embodiments can be accomplished using the teachings ofthe present invention and that the invention is not limited to theembodiments illustrated for explanatory purposed.

First Embodiment 1. Configuration of Liquid Crystal Display Device

FIG. 1 is a block diagram showing a configuration of a liquid crystaldisplay device according to a first embodiment of the present invention.A liquid crystal display device 1 according to the present inventionincludes an LCD panel 2 and a LCD driver 3. The LCD panel 2 includesdata lines, gate lines, and pixels arranged in v rows by H columns. Hpixels are provided on one horizontal line of the LCD panel 2. Eachpixel includes three sub-pixels, namely, a sub-pixel corresponding tored (R sub-pixel), a sub-pixel corresponding to green (G sub-pixel), anda sub-pixel corresponding to blue (B sub-pixel). Each sub-pixel isarranged on a point where the data line and the gate line intersect oneanother. The LCD driver 3 drives each sub-pixel of the LCD panel 2 inresponse to image data Din received from a processing device 4 todisplay a desired image. An operation of the LCD driver 3 is controlledby control signals 5 supplied from the processing device 4. As theprocessing device 4, a CPU (Central Processing Unit), for example, isused.

The LDC driver 3 includes a command control circuit 11, a line memory12, an image compression circuit 13, an image memory 14, an imagedecompression circuit 15, a data line drive circuit 16, a gate linedrive circuit 17, a timing control circuit 18, and a gradation voltagegeneration circuit 19.

The command control circuit 11 has following three functions. Firstly,the command control circuit 11 supplies timing setup data 21 indicatingan operational timing of the LCD driver 3 to the timing control circuit18. Secondly, the command control circuit 11 supplies, to the gradationvoltage generation circuit 19, gradation setup data 22 used for settinga relationship (that is, the γ curve) between: a voltage level of adriving voltage supplied to the LCD panel 2; and a gradation value shownin the image data Din.

Thirdly, the command control circuit 11 has a function for transferringthe image data Din supplied from the processing device 4 to the imagecompression circuit 13. In this state, the command control circuit 11transfers the image data Din in units of pixels of 2 rows by 2 columnsto the image compression circuit 13. Since the image data is normallysent to the LCD driver in the order from pixels on an upper horizontalline, the image data Din has to be rearranged to transfer the image dataDin in units of pixels of 2 rows by 2 columns to the image compressioncircuit 13. To perform this rearrangement, the command control circuit11 includes the line memory 12 having a capacity for retention of theimage data Din of pixels on one horizontal line.

FIG. 2 is a view showing a method for transferring the image data Din tothe image compression circuit 13. The image data Din is data indicatinga gradation of each pixel. The image data Din, in the presentembodiment, is 24-bit data representing gradations of the R sub-pixel,the G sub-pixel, and the B sub-pixel by 8 bits, respectively. When theimage data Din of pixels on an odd-number horizontal line issequentially supplied to the LCD driver 3, the command control circuit11 stores the supplied image data Din in the line memory 12.Subsequently, when the image data Din of the left-end pixel and thesecond-left pixel on the odd-number horizontal line is supplied to theLCD driver 3, the image data Din of the left-end pixel and thesecond-left pixel on the odd-number horizontal line and the image dataDin of the left-end pixel and the second-left pixel on the even-numberhorizontal line are collectively transferred to the image compressioncircuit 13. That is, image data of the leftmost pixels in 2 rows by 2columns is transferred to the image compression circuit 13.Subsequently, when the image data Din of the third-left pixel and thefourth-left pixel on the even-number horizontal line is supplied to theLCD driver 3, the image data Din of the third-left pixel and thefourth-left pixel on the odd-number horizontal line and the image dataDin of the third-left pixel and the fourth-left pixel on the even-numberhorizontal line are collectively transferred to the image compressioncircuit 13. That is, image data of the second-left pixels in 2 rows by 2columns are transferred to the image compression circuit 13. Then, theimage data Din are transferred to the image compression circuit 13 inthe same manner.

The image compression circuit 13 performs an image compression processfor the image data Din sent from the command control circuit 11. Theimage compression process by the image compression circuit 13 isperformed in units of pixels in 2 rows by 2 columns. Hereinafter, thepixels in 2 rows by 2 columns that constitute a unit of the imagecompression process are referred to as a “block”, and a block to whichthe image compression processing is performed is referred to as a“target block”. When the image data Din of pixels of a target block aresent from the command control circuit 11, the image compression processis performed to the sent image data Din, thereby compressed image datais generated.

In the present embodiment, the compressed image data generated by theimage compression circuit 13 is data representing gradations of 4 pixelsconstituting a block by 48 bits. Since the original image data Dinrepresents the gradations of 4 pixels by 96 (=24×4) bits, the imagecompression process by the image compression circuit 13 reduces a dataamount by half. That is, the number of bits of compressed image datagenerated regarding a certain block is half of the number of bits of theimage data Din before the compression of the block. This is favorablewhen the image memory 14 is used for various uses. For example, a casewhere the image memory 14 has a size of V×H×24 bits will be considered.In this case, the image memory 14 is able to store data of 2 framesregarding compressed image data, but is able to store data of 1 frameregarding the original image data Din. In this case, an overdriveprocess for a moving image can be performed by storing, regarding astill image, the image data Din to the image memory 14 withoutcompressing the image data Din, and by storing, regarding a movingimage, compressed image data of two frames, a previous frame and apresent frame, to the image memory 14. Here, the overdrive process is atechnique for improving a response speed of a liquid crystal by driving:a voltage higher than normal voltage in a case of the driving in apositive voltage; and a voltage lower than normal voltage in a case ofthe driving in a negative voltage when a gradation has widely changed.In the case where the liquid crystal display device 1 is configured inthis manner, the image compression circuit 13 stores, regarding a stillimage, the image data Din to the image memory 14 without compressing theimage data Din and stores, regarding a moving image, compressed imagedata generated by compressing the image data Din to the image memory 14.

The image compression circuit 13 is an image processing circuitconfigured so that an image compression process can be performed by aplurality of compression methods. The image compression circuit 13selects an appropriate compression method based on a correlation ofimage data of pixels arranged in 2 rows by 2 columns of a target block,and performs the image compression process by using the selectedcompression method. A configuration and an operation of the imagecompression circuit 13 will be explained below in detail.

The image memory 14 stores compressed image data generated by the imagecompression circuit 13. In the present embodiment, the image memory 14has a size of (V/2)×(H/2)×48 bits. To enable the overdrive process to beperformed to a moving image as described above, the image memory 14 maybe configured to have a size of V×H×24 bits.

The image decompression circuit 15 decompresses compressed image dataread from the image memory 14 to generate decompressed image data. Inthe present embodiment, the decompressed image data is 24-bit datarepresenting gradations of red, green, and blue by 8 bits, respectively.A configuration and an operation of the image decompression circuit 15will be explained below in detail. The generated decompressed image datais sent to the data line drive circuit 16.

The data line drive circuit 16 drives the LCD panel 2 in response to thedecompressed image data sent from the image decompression circuit 15.Specifically, the data line drive circuit 16 includes a shift register16 a, a display latch 16 b, and a drive circuit 16 c. The shift register16 a sequentially receives the decompressed image data from the imagecompression circuit 15 and stores the received data. The shift register16 a has a capacity for retaining decompressed image data of H pixels onone horizontal line. The display latch 16 b temporarily latches thedecompressed image data of pixels of one horizontal line (H pixels)retained by the shift register 16 a, and transfers the latcheddecompressed image data to the drive circuit 16 c. Operational timingsof the shift register 16 a and the display latch 16 b are controlled bya timing control signal 23 supplied from the timing control circuit 18.The drive circuit 16 c drives a corresponding data line of the LCD panel2 in response to the decompressed image data of one line sent from thedisplay latch 16 b. More specifically, the drive circuit 16 c selects acorresponding gradation voltage from among a plurality of gradationvoltages V₁ to V_(m) supplied from the gradation voltage generationcircuit 19 in response to the decompressed image data, and drives thecorresponding data line of the LCD panel 2 to be the selected gradationvoltage.

The gate line drive circuit 17 drives a gate line of the LCD panel 2. Anoperational timing of the gate line drive circuit 17 is controlled by atiming control signal 24 sent from the timing control circuit 18.

The timing control circuit 18 performs a timing control on whole of theLCD driver 3 in response to the timing setup data 21 sent from thecommand control circuit 11. More specifically, the timing controlcircuit 18 controls operational timing of the data line drive circuit 16by supplying the timing control signal 23 to the data line drive circuit16, and controls an operational timing of the gate line drive circuit 17by supplying the timing control signal 24 to the gate line drive circuit17.

The gradation voltage generation circuit 19 generates the gradationvoltages V₁ to V_(m) in response to the gradation setup data 22 receivedfrom the command control circuit 11, and supplies the voltages to thedata line drive circuit 16. Voltage levels of the gradation voltages V₁to V_(m) are controlled based on the gradation setup data 22.

Configurations and operations of the image compression circuit 13 andthe image decompression circuit 15 will be subsequently explained.

When receiving image data of pixels in 2 rows by 2 columns of a targetblock from the command control circuit 11, the image compression circuit13 compresses the received image data by using any one of the following4 compression methods,

(1×4) pixel compression,

(2+1×2) pixel compression,

(2×2) pixel compression, and

(4×1) pixel compression.

Here, the (1×4) pixel compression is a method for performing a processto reduce the number of bit planes independently to each of all 4 pixelsof a target block. This (1×4) pixel compression is favorable in a casewhere a correlation of image data of 4 pixels is low. The (2+1×2) pixelcompression is a method for determining a representative valuerepresenting image data of 2 pixels of all 4 pixels of a target blockand for performing a process (in the present invention, the ditherprocessing using a dither matrix) to reduce the number of bit planesregarding each of other two pixels. This (2+1×2) pixel compression isfavorable in a case where a correlation of image data of two pixels offour pixels is high and a correlation of image data of other two pixelsis low. The (2×2) pixel compression is a method for, after separatingall four pixels of a target block into two groups including two pixelsand determining a representative value representing image data regardingeach group of two pixels, compressing the image data. This (2×2) pixelcompression is favorable in a case where a correlation of image data oftwo pixels of four pixels is high and a correlation of image data ofother two pixels is high. The (4×1) pixel compression is a method for,after determining a representative value representing image data of fourpixels of a target block, compressing the image data. This (4×1) pixelcompression is favorable in a case where a correlation of image data ofall four pixels of the target block is high. Details of theabove-mentioned four compression methods will be described later.

One feature of the liquid crystal display device 1 according to thepresent embodiment is to accept a compression method (in the presentembodiment, the 2+1×2 pixel compression and the (2×2) pixel compression)for calculating a representative value corresponding to image data of aplurality of pixels (not all) of a target block, in addition to acompression method (in the present embodiment, (4×1) pixel compression)for calculating a representative value corresponding to image data ofall pixels of a target block and a compression method (in the presentembodiment, (1×4) pixel compression) for performing a process to reducethe number of bit planes independently to each of all 4 pixels of atarget block. This is effective in reducing block noise and granularnoise. As described above, when the compression method for performingthe process to reduce the number of bit planes independently to a pixelhaving a high correlation of image data is performed, granular noise isgenerated, and meanwhile when the block coding is performed to a pixelhaving a low correlation of image data, block noise is generated. Theliquid crystal display device 1 according to the present embodimentaccepting the compression method for calculating a representative valuecorresponding to image data of a plurality of pixels (not all) of atarget block can avoid a case where: the process to reduce the number ofbit planes is performed to the pixel having the high correlation ofimage data; or the block coding is performed to the pixel having the lowcorrelation of image data. Accordingly, the liquid crystal displaydevice 1 according to the present embodiment is able to reduce blocknoise and granular noise.

Determination as to which one of four compressions is used is made onthe basis of a correlation of image data of pixels in 2 rows by 2columns. For example, the (4×1) pixel compression is used in a casewhere a correlation of image data of all four pixels in 2 rows by 2columns is high, and the (2×2) pixel compression is used in a case wherea correlation of image data of two pixels of four pixels is high and acorrelation of image data of other two pixels is high. Details ofselection of the compression methods will be described below.

To perform the above-mentioned operation, the image compression circuit13 includes a form recognition portion 31, a (1×4) pixel compressionportion 32, a (2+1×2) pixel compression portion 33, a (2×2) pixelcompression portion 34, a (4×1) pixel compression portion 35, and acompression data selection portion 37.

The form recognition portion 31 receives image data of pixels in 2 rowsby 2 columns from the command control circuit 11, and recognizes acorrelation of the received image data of pixels in 2 rows by 2 columns.For example, the form recognition portion 31 recognizes: which one ofcombinations of pixels of the pixels in 2 rows by 2 columns realizes ahigher correlation of image data; or which pixel has a low correlationof image data with respect to other pixels. Moreover, the formrecognition portion 31, in response to the recognition result, generatesform recognition data to instruct which one of the four compressionmethods, (1×4) pixel compression, (2+1×2) pixel compression, (2×2) pixelcompression, and (4×1) pixel compression should be used.

The (1×4) pixel compression portion 32, (2+1×2) pixel compressionportion 33, (2×2) pixel compression portion 34, and (4×1) pixelcompression portion 35 perform the above-mentioned (1×4) pixelcompression, (2+1×2) pixel compression, (2×2) pixel compression, and(4×1) pixel compression, respectively, and generates (1×4) compresseddata, (2+1×2) compressed data, (2×2) compressed data, and (4×1)compressed data, respectively.

Based on the form recognition data sent from the form recognitionportion 31, the compression data selection portion 37 outputs any one ofthe (1×4) compressed data, the (2+1×2) compressed data, the (2×2)compressed data, and the (4×1) compressed data as compressed image datato the image memory 14. The compressed image data includes acompression-type recognition bit that indicates which one of theabove-mentioned four compression methods was used. The image memory 14stores the compressed image data received from the compression dataselection portion 37.

The image decompression circuit 15 determines which one of theabove-mentioned four compression methods compressed the compressed imagedata read from the image memory 14, and decompresses the compressedimage data by using a decompression method corresponding to acompression method used for the compression. To perform such operations,the image decompression circuit 15 includes a (1×4) pixel decompressionportion 41, a (2+1×2) pixel decompression portion 42, a (2×2) pixeldecompression portion 43, a (4×1) pixel decompression portion 44, and animage data selection portion 45. The (1×4) pixel decompression portion41, (2+1×2) pixel decompression portion 42, (2×2) pixel decompressionportion 43, and (4×1) pixel decompression portion 44 have a function fordecompressing compressed image data compressed by the (1×4) pixelcompression, (2+1×2) pixel compression, (2×2) pixel compression, and(4×1) pixel compression, respectively. The image data selection portion45 recognizes the compression method actually used for the compressionon the basis of the compression type recognition bit included incompressed image data, and selects, as decompressed image data, datadecompressed and generated by the decompression method corresponding tothe compression method actually used for the compression from amongimage data outputted from the (1×4) pixel decompression portion 41, the(2+1×2) pixel decompression portion 42, the (2×2) pixel decompressionportion 43, and the (4×1) pixel decompression portion 44. Thedecompressed image data is supplied to the data line drive circuit 16and is used to drive the LCD panel 2.

In what follows, details of: a method for recognizing a correlation ofimage data of pixels in 2 rows by 2 columns; and the above-mentionedfive compression methods will be explained. In the followingexplanation, as shown in FIG. 3, in the pixels in 2 rows by 2 columns,an upper left pixel is referred to as a pixel A, an upper right pixel isreferred to as a pixel B, an lower left pixel is referred to as a pixelC, and an lower right pixel is referred to as a pixel D. In addition,gradation values of the R sub-pixels of the pixels A, B, C, and D arewritten as R_(A), R_(B), R_(C), and R_(D), respectively, gradationvalues of the G sub-pixels of the pixels A, B, C, and D are written asG_(A), G_(B), G_(C), and G_(D), respectively, and gradation values ofthe B sub-pixels of the pixels A, B, C, and D are written as B_(A),B_(B), B_(C), and B_(D), respectively.

2. Method for Recognizing a Correlation

In the method for recognizing a correlation by the form recognitionportion 31 of the image compression circuit 13, it is judged which oneof following cases is applied to image data of target 4 pixels in 2 rowsby 2 columns.

Case A: A correlation between image data of arbitrarily-combined pixelsof four pixels is low (FIG. 4A).

Case B: There is a high correlation between image data of two pixels,and image data of other two pixels have a low correlation with theformer two pixels and have a low correlation with each other (FIG. 4B).

Case C: There is a high correlation between image data of two pixels,and there is a high correlation between image data of other two pixels(FIG. 4C).

Case D: There is a high correlation of image data of four pixels (FIG.4D).

FIG. 5 is a flowchart showing the method for recognizing a correlationaccording to the present embodiment.

At first, when the following condition (A) is not satisfied with respectto all combinations of i and j; wherein

iε{A, B, C, D},

jε{A, B, C, D}, and

j≠i,

the form recognition portion 31 judges this matter is applied to thecase A (that is, correlation between image data of arbitrarily-combinedpixels of four pixels is low) (Step S01).

Condition (A):

|Ri−Rj|≦Th1,

|Gi−Gj|≦Th1, and

|Bi−Bj|≧Th1.

When the matter is applied to the case A, the form recognition portion31 determines to perform the (1×4) pixel compression. Here, Th1 is apredetermined value.

When the matter is not applied to the case A, the form recognitionportion 31 defines two pixels of a first combination and the other twopixels of a second combination regarding four pixels, and judges whetheror not the following condition is satisfied regarding the allcombinations. The condition is that: a difference between image data oftwo pixels of the first combination is smaller than a predeterminedvalue; and a difference between image data of two pixels of the secondcombination is smaller than a predetermined value. More specifically,the form recognition portion 31 judges whether or not the followingconditions (B1) to (B3) are satisfied (Step S02).

Condition (B1):

|R_(A)−R_(B)|≦Th2,

|G_(A)−G_(B)|≦Th2,

|B_(A)−B_(B)|≦Th2,

|R_(C)−R_(D)|≦Th2,

|G_(C)−G_(D)|≦Th2, and

|B_(C)−B_(D)|≦Th2.

Condition (B2):

|R_(A)−R_(C)≦Th2,

G_(A)−G_(C)≦Th2,

B_(A)−B_(C)≦Th2,

|R_(B)−R_(D)|≦Th2,

G_(B)−G_(D)≦Th2, and

|B_(B)−B_(D)|≦Th2.

Condition (B3):

|R_(A)−R_(D)|≦Th2,

|G_(A)−G_(D)|≦Th2,

|B_(A)−B_(D)|≦Th2,

|R_(B)−R_(C)|≦Th2,

|G_(B)−G_(C)|≦Th2, and

|B_(B)−B_(C)|≦Th2.

When any one of the above-mentioned conditions (B1) to (B3) is notsatisfied, the form recognition portion 31 recognizes the matter isapplied to the case B (that is, there is a high correlation betweenimage data of two pixels and image data of other two pixels have a lowcorrelation with each other). In this instance, the form recognitionportion 31 determines to perform the (2+1×2) pixel compression. Here,Th2 is a predetermined value.

When it is determined that the matter is not applied to both of thecases A and B, the form recognition 31 judges whether or not thefollowing condition is satisfied regarding all colors of the fourpixels. The condition is that a difference between a maximum value and aminimum value of image data of four pixels is smaller than apredetermined value. More specifically, the form recognition portion 31judges whether or not a following condition (C) is satisfied (Step S03).

Condition (C):

max (R_(A), R_(B), R_(C), R_(D))−min (R_(A), R_(B), R_(C), R_(D))<Th3,

max (G_(A), G_(B), G_(C), G_(D))−min (G_(A), G_(B), G_(C), G_(D))<Th3,and

max (B_(A), B_(B), B_(C), B_(D))−min (B_(A), B_(B), B_(C), B_(D))<Th3.

When the condition (C) is not satisfied, the form recognition portion 31determines the matter is applied to the case C (that is, there is a highcorrelation between image data of two pixels, and there is a highcorrelation between image data of other two pixels). In this instance,the form recognition portion 31 determines to perform the (2×2) pixelcompression. Here, Th3 is a predetermined value.

Meanwhile, when the condition (C) is not satisfied, the form recognitionportion 31 determines that the matter is applied to the case D (there isa high correlation of image data of four pixels). In this instance, theform recognition portion 31 determines to perform the (4×1) pixelcompression.

Based on the above-mentioned recognition result of the correlation, theform recognition portion 31 generates form recognition data to instructwhich one of the (1×4) pixel compression, the (2+1×2) pixel compression,the (2×2) pixel compression, and the (4×1) pixel compression should beused and sends the generated data to the compression data selectionportion 37. As described above, based on the form recognition data sentfrom the form recognition portion 31, the compression data selectionportion 37 outputs any one of the (1×4) compressed data, (2+1×2)compressed data, (2×2) compressed data, and (4×1) compressed data ascompressed image data to the image memory 14.

3. Details of Compression Method and Decompression Method

The (1×4) pixel compression, the (2+1×2) pixel compression, the (2×2)pixel compression, the (4×1) pixel compression, and decompressionmethods of compressed image data compressed these compression methodswill be subsequently explained.

3-1. (1×4) Pixel Compression and Decompression Thereof

FIG. 6A is a schematic view to explain the (1×4) image compression, andFIG. 7 is a schematic view showing a format of (1×4) compressed data. Asdescribed above, the (1×4) pixel compression is a compression methodemployed when a correlation between image data of arbitrarily-combinedpixels of four pixels is low. As shown in FIG. 7, in the presentembodiment, the (1×4) compressed data includes: a compression typerecognition bit; R_(A) data, G_(A) data, and B_(A) data corresponding toimage data of the pixel A; R_(B) data, G_(B) data, and B_(B) datacorresponding to image data of the pixel B; R_(C) data, G_(C) data, andB_(C) data corresponding to image data of the pixel C; and R_(D) data,G_(D) data, and B_(D) data corresponding to image data of the pixel D.The (1×4) compressed data is 48-bit data. Here, the compression typerecognition bit is data that indicates a type of compression method usedfor a compression, and one bit is allocated to the compression typerecognition bit in the (1×4) compressed data. In the present embodiment,a value of the compression type recognition bit of the (1×4) compresseddata is “0”.

Meanwhile, R_(A) data, G_(A) data, and B_(A) data are bit planereduction data obtained by performing a process to reduce bit planes ongradation values of an R sub-pixel, a G sub-pixel, and a B sub-pixel ofthe pixel A, and R_(B) data, G_(B) data, and B_(B) data are bit planereduction data obtained by performing a process to reduce bit planes ongradation values of an R sub-pixel, a G sub-pixel, and a B sub-pixel ofthe pixel B. Similarly, R_(C) data, G_(C) data, and B_(C) data are bitplane reduction data obtained by performing a process to reduce bitplanes on gradation values of an R sub-pixel, a G sub-pixel, and a Bsub-pixel of the pixel C, and R_(D) data, G_(D), data and B_(D) data arebit plane reduction data obtained by performing a process to reduce bitplanes on gradation values of a R sub-pixel, a G sub-pixel, and a Bsub-pixel of the pixel D. In the present embodiment, only the B_(D) datacorresponding to the B sub-pixel of the pixel D is 3-bit data, andothers are 4-bit data.

Referring to FIG. 6A, the (1×4) pixel compression will be explainedbelow. In the (1×4) pixel compression, the dither processing using thedither matrix is performed on each of the pixels A to D, thereby thenumber of bit planes of image data of each of the pixels A to D isreduced. Specifically, a process to add error data a to each of imagedata of pixels A, B, C, and D is performed at first. In the presetembodiment, the error data a (alpha) of each pixel is determined on thebasis of coordinates of the pixel by using a basic matrix, theBayer-Matrix. The calculation of the error data a will be describedlater. Here, the explanation will be performed supposing that the errordata a determined for the pixels A, B, C, and D are 0, 5, 10, and 15,respectively.

Moreover, a rounding process and a bit round-down process are performed,thereby R_(A) data, G_(A) data, and B_(A) data, R_(B) data, G_(B) data,and B_(B) data, R_(C) data, G_(C) data, and B_(C) data, and R_(D) data,G_(D) data, and B_(D) data are generated. Specifically, as for agradation value of the B sub-pixel of the pixel D, a process to roundlower 5 bits down is performed after adding a value 16. As for each ofother gradation values, a process to round lower 4 bits down isperformed after adding a value 8. By adding a value “0” as a compressiontype recognition bit to the R_(A) data, the G_(A) data, and the B_(A)data, the R_(B) data, the G_(B) data, and the B_(B) data, the R_(C)data, the G_(C) data, and the B_(C) data, and the R_(D) data, the G_(D)data, and the B_(D) data each generated in this manner, (1×4) compresseddata is generated.

FIG. 6B is a view showing a decompression method of compressed imagedata compressed by the (1×4) pixel compression. In a decompression ofthe compressed image data compressed by the (1×4) pixel compression,rounding up of bits of the R_(A) data, the G_(A) data, and the B_(A)data, the R_(B) data, the G_(B) data, and the B_(B) data, the R_(C)data, the G_(C) data, and the B_(C) data, and the R_(D) data, the G_(D)data, and the B_(D) data is firstly performed. Specifically, as for theB_(D) data corresponding to the B sub-pixel of the pixel D, rounding upof 5 bits is performed, and as for other data, rounding up of 4 bits isperformed.

Furthermore, subtraction of the error data a is performed, thereby imagedata of pixels A to D (that is, gradation values of R sub-pixel, Gsub-pixel, and B sub-pixel) are extracted. Comparing image data ofpixels A to D in a rightmost table of FIG. 6B with image data of pixelsA to D in a leftmost table of FIG. 6A, it can be understood thatoriginal image data of pixels A to D are almost extracted by theabove-mentioned decompression method.

3-2. (2+1×2) Pixel Compression

FIG. 8A is a conceptual view to explain the (2+1×2) pixel compression,and FIG. 9A is a conceptual view showing a format of the (2+1×2)compressed data. As described above, the (2+1×2) pixel compression isemployed when there is a high correlation between image data of twopixels, and image data of other two pixels have a low correlation withthe former two pixels and have low correlation with each other. As shownin FIG. 9A, in the present embodiment, the (2+1×2) compressed dataincludes: a compression type recognition bit; form recognition data; a Rrepresentative value; a G representative value; a B representativevalue; large-small recognition data; β (beta) comparison result data;R_(i) data, G_(i) data, and B_(i) data; and R_(j) data, G_(j) data, andB_(j) data. The (2+1×2) compressed data is 48-bit data same as theabove-mentioned (1×4) compressed data.

The compression type recognition bit is data that indicates a type ofcompression method used for compression, and 2 bits are allocated to thecompression type recognition bit in the (2+1×2) compressed data. In thepresent embodiment, a value of the compression type recognition bit ofthe (2+1×2) compressed data is “10”.

The form recognition data is 3-bit data that indicates which one ofcorrelations between image data of two pixels of the pixels A to D ishigh. When the (2+1×2) pixel compression is employed, one of acorrelation of image data between two pixels of the pixels A to D ishigh and a correlation of image data of remaining two pixels with theformer two pixels is low. Accordingly, there are six combinations of twopixels having a high correlation of image data as follows;

the pixels A and C,

the pixels B and D,

the pixels A and B,

the pixels C and D,

the pixels B and C, and

the pixels A and D.

The form recognition data indicates which one of the six combinations isa combination of the two pixels having a high correlation between imagedata by using 3 bits.

The R representative value, the G representative value, and the Brepresentative value are values representing gradation values of an Rsub-pixel, a G sub-pixel, and a B sub-pixel of two pixels having a highcorrelation, respectively. In an example of FIG. 9A, the Rrepresentative value and the G representative value are 5-bit or 6-bitdata, and the B representative value is 5-bit data.

β comparison data is data that indicates whether or not a differencebetween gradation values of R sub-pixels of two pixels having a highcorrelation and a difference between image data of G sub-pixels of thetwo pixels having a high correlation are greater than a predeterminedthreshold value β. In the present embodiment, the β comparison data is2-bit data. Meanwhile, the large-small recognition data is data thatindicates: which one of the gradation values of the R sub-pixels of thetwo pixels having a high correlation is larger; and which one of thegradation values of the G sub-pixels of the two pixels is larger. Thelarge-small recognition data corresponding to the R sub-pixel isgenerated only when the difference between gradation values of Rsub-pixels of two pixels having a high correlation is larger than thethreshold value β, and the large-small recognition data corresponding tothe G sub-pixel is generated only when the difference between gradationvalues of G sub-pixels of two pixels having a high correlation is largerthan the threshold value β.

Accordingly, the large-small recognition data is 0 to 2-bit data.

The R_(i) data, the G_(i) data, and the B_(i) data and the R_(j) data,the G_(j) data, and the B_(j) data are bit plane reduction data obtainedby performing a process to reduce bit planes on gradation values of theR sub-pixel, the G sub-pixel, and the B sub-pixel of two pixels having alow correlation.

In the present embodiment, each of: the R_(i) data, the G_(i) data, andthe B_(i) data; and the R_(j) data, the G_(j) data, and the B_(j) datais 4-bit data.

Referring to FIG. 8A, the (2+1×2) pixel compression will be explainedbelow. FIG. 8A describes generation of the (2+1×2) compressed data in acase where: a correlation between image data of the pixels A and B ishigh; image data of the pixels C and D have a low correlation with imagedata of the pixels A and B; and image data of the pixels C and D have alow correlation with each other. A person skilled in the art will easilyunderstand that the (2+1×2) compressed data can be generated in the samemanner also in other cases.

A process to compress image data of the pixels A and B (having a highcorrelation) will be firstly explained. First of all, regarding each ofthe R sub-pixel, the G sub-pixel, and the B sub-pixel, an average valueof gradation values is calculated. The average values Rave, Gave, andBave of the gradation values of the R sub-pixel, the G sub-pixel, andthe B sub-pixel are calculated by the following expressions,

Rave=(R _(A) +R _(B)+1)/2,

Gave=(G _(A) +G _(B)+1)/2,

Bave=(B _(A) +B _(B)+1)/2.

In addition, comparisons are performed whether or not a difference|R_(A)−R_(B)| of gradation values of R sub-pixels of the pixels A and Band a difference |G_(A)−G_(B)| of gradation values of G sub-pixels arerespectively larger than the predetermined threshold value β. Thiscomparison result is described in the (2+1×2) compressed data as the fcomparison data.

Moreover, in a following procedure, large-small recognition data relatedto the R sub-pixel and G sub-pixel of the pixels A and B are created.When the difference |R_(A)−R_(B)| of gradation values of R sub-pixels ofthe pixels A and B is larger than the threshold value β, it is describedto the large-small recognition data which one of gradation values of theR sub-pixels of the pixels A and B is larger. When the difference|R_(A)−R_(B)| of gradation values of R sub-pixels of the pixels A and Bis equal to or less than the threshold value β, the magnitude relationof the gradation values of the R sub-pixels of the pixels A and B is notdescribed in the large-small recognition data.

In the same manner, when the difference |G_(A)−G_(B)| of gradationvalues of G sub-pixels of the pixels A and B is larger than thethreshold value β, it is described to the large-small recognition datawhich one of gradation values of the G sub-pixels of the pixels A and Bis larger. When the difference |G_(A)−G_(B)| of gradation values of Gsub-pixels of the pixels A and B is equal to or less than the thresholdvalue β, the magnitude relation of the gradation values of the Gsub-pixels of the pixels A and B is not described in the large-smallrecognition data.

In the example of FIG. 8A, the gradation values of the R sub-pixels ofthe pixels A and B are 50 and 59, respectively, and the threshold valueβ is 4. In this instance, since the difference |R_(A)−R_(B)| of thegradation values is larger than the threshold value β, the result isdescribed in the β comparison data, and it is described to thelarge-small recognition data that the gradation value of the R sub-pixelof the pixel B is larger than the gradation value of the R sub-pixel ofthe pixel A. Meanwhile, the gradation values of the G sub-pixels of thepixels A and B are 2 and 1, respectively. Since the difference|G_(A)−G_(B)| of the gradation values is equal to or less than thethreshold value β, the result is described in the β comparison data. Themagnitude relation of the gradation values of the G sub-pixels of thepixels A and B is not described in the large-small recognition data. Asthe result, in the example of FIG. 8A, the large-small recognition datais 1-bit data.

Subsequently, the error data a is added to average values Rave, Gave,and Bave of the gradation values of the R sub-pixel, the G sub-pixel,and B sub-pixel. In the present embodiment, the error data a isdetermined on the basis of coordinates of the two pixels of eachcombination by using a basic matrix. The calculation of the error data awill be described below. Supposing that the error data a determined forthe pixels A and B is “0”, the present embodiment will be explainedbelow.

Moreover, a rounding process and a bit round-down process are performed,thereby the R representative value, the G representative value, and theB representative value are calculated. Specifically, a value added inthe rounding processes regarding the R sub-pixel and the G sub-pixel andthe number of bits rounded down in the bit round-down process aredetermined depending on the magnitude relation of the threshold value βwith the differences |R_(A)−R_(B)| and |G_(A)−G_(B)| of the gradationvalues. As for the R sub-pixel, when the difference |R_(A)−R_(B)| of thegradation values of R sub-pixels is larger than the threshold value β, aprocess to round lower 3 bits down after adding a value 4 to the averagevalue Rave of the gradation values of the R sub-pixels is performed,thereby the R representative value is calculated. When the difference|R_(A)−R_(B)| is not larger than the threshold value β, a process toround lower 2 bits down after adding a value 2 to the average value Raveis performed, thereby the R representative value is calculated. In thesame manner, also as for the G sub-pixel, when the difference|G_(A)−G_(B)| of the gradation values is larger than the threshold valueβ, a process to round lower 3 bits down after adding a value 4 to theaverage value Gave of the gradation values of the G sub-pixels isperformed, thereby the G representative value is calculated. When thedifference |G_(A)−G_(B)| is not larger than the threshold value β, aprocess to round lower 2 bits down after adding a value 2 to the averagevalue Gave is performed, thereby the G representative value iscalculated. In the example of FIG. 8A, as for the average value Rave ofthe R sub-pixel, a process to round lower 3 bits down after adding avalue 4 is performed, and as for the average value Gave of the Gsub-pixel, a process to round lower 2 bits down after adding a value 2is performed.

Meanwhile, as for the B sub-pixel, a process to round lower 3 bits downafter adding a value 4 to the average value Bave of the gradation valuesof the B sub-pixels is performed, thereby the B representative value iscalculated. As described above, compression processes of image data ofthe pixels A and B are completed.

As for image data of the pixels C and D (having a low correlation), aprocess same as that of the (1×4) pixel compression is performed. Thatis, the dither processing using a dither matrix is performedindependently on each of the pixels C and D, thereby the number of bitplanes of image data of each of the pixels C and D is reduced.Specifically, a process to add the error data a to each of image data ofthe pixels C and D is firstly performed. As described above, the errordata a of each pixel is calculated from the coordinates of the pixels.Supposing that the error data a determined for the pixels C and D are 10and 15, respectively, the explanation will be continued below.

Moreover, a rounding process and a bit round-down process are performed,thereby R_(C) data, G_(C) data, and B_(C) data, and R_(D) data, G_(D)data, and B_(D) data are generated. Specifically, a process to roundlower 4 bits down after adding a value 8 to each of the gradation valuesof the R sub-pixel, the G sub-pixel, and the B sub-pixel of each of thepixels C and D is performed. In this manner, the R_(C) data, the G_(C),data and the B_(C) data and the R_(D) data, the G_(D) data, and theB_(D) data are calculated.

By adding the compression type recognition bit and the form recognitiondata to the R representative value, the G representative value, the Brepresentative value, the large-small recognition data, the β comparisonresult data, the R_(C) data, the G_(C) data, and the B_(C) data, and theR_(D) data, the G_(D) data, and the B_(D) data each generated in theabove-mentioned manner, the (2+1×2) compression data is generated.

FIG. 8B is a view showing a decompression method of the compressed imagedata compressed in the (2+1×2) pixel compression. FIG. 8B describesdecompression of the (2+1×2) compressed data in a case where: acorrelation between image data of the pixels A and B is high; image dataof the pixels C and D have a low correlation with image data of thepixels A and B; and image data of the pixels C and D have a lowcorrelation with each other. A person skilled in the art will easilyunderstand that the (2+1×2) compressed data can be decompressed in thesame manner also in other cases.

A process to decompress image data of the pixels A and B (having a highcorrelation) will be firstly explained. First of all, a bit round-upprocess is performed on each of the R representative value, the Grepresentative value, and the B representative value. The number of bitsof the bit round-up process to each of the R representative value andthe G representative value is determined depending on the magnituderelation of the threshold value β with each of the differences|R_(A)−R_(B)| and |G_(A)−G_(B)| of the gradation values, the magnituderelation being described in the β comparison data. When the difference|R_(A)−R_(B)| of gradation values of R sub-pixels is larger than thethreshold value β, the bit round-up process of 3 bits is performed onthe R representative value, and when the difference |R_(A)−R_(B)| is notlarger than the threshold value β, the bit round-up process of 2 bits isperformed. In the same manner, when the difference |G_(A)−G_(B)| ofgradation values of G sub-pixels is larger than the threshold value β,the bit round-up process of 3 bits is performed on the G representativevalue, and when the difference |G_(A)−G_(B)| is not larger than thethreshold value β, the bit round-up process of 2 bits is performed. Inthe example of FIG. 8B, regarding the R representative value, theprocess to round 3 bits up is performed, and regarding the Grepresentative value, the process to round 2 bits up is performed.Meanwhile, regarding the B representative value, the process to round 3bits up is performed.

In addition, after subtraction of the error data α is performed on eachof the R representative value, the G representative value, and the Brepresentative value, a process to extract the gradation values of theR, G, and B sub-pixels of the pixels A and B from the R representativevalue, the G representative value, and the B representative value isperformed.

In the extraction of the gradation values of the R sub-pixels of thepixels A and B, the β comparison data and the large-small recognitiondata are used. When it is described in the β comparison data that thedifference |R_(A)−R_(B)| of the gradation values of the R sub-pixels islarger than the threshold value β, a value obtained by adding a constantvalue 5 to the R representative value is extracted as the gradationvalue of the R sub-pixel of larger one of the pixels A and B describedin the large-small recognition data, and a value obtained by subtractinga constant value 5 from the R representative value is extracted as thegradation value of the R sub-pixel of smaller one of the pixels A and Bdescribed in the large-small recognition data. On the other hand, whenthe difference |R_(A)−R_(B) of the gradation values of the R sub-pixelsis smaller than the threshold value β, the gradation values of the Rsub-pixels of the pixels A and B is extracted as being equal to the Rrepresentative value. In the example of FIG. 8B, the gradation value ofthe R sub-pixel of the pixel A is extracted as a value obtained bysubtracting a value 5 from the R representative value, and the gradationvalue of the R sub-pixel of the pixel B is extracted as a value obtainedby adding a value 5 to the R representative value.

Also in an extraction of the gradation values of the G sub-pixels of thepixels A and B, the same process is Performed by using the β comparisondata and the large-small recognition data. In the example of FIG. 8B,both of values of the G sub-pixels of the pixels A and B are extractedas being equal to the G representative value.

On the other hand, in an extraction of the gradation values of the Bsub-pixels of the pixels A and B, independently of the β comparison dataand the large-small recognition data, both of values of the B sub-pixelsof the pixels A and B are extracted as being equal to the Brepresentative value.

In the above-described manner, the extraction of the gradation values ofthe R sub-pixels, G sub-pixels, and B sub-pixels of the pixels A and Bis completed.

In a decompression process regarding image data of the pixels C and D(having a low correlation), the same process as the above-mentioneddecompression process of the (1×4) compressed data is performed. In thedecompression process regarding image data of the pixels C and D, a bitround-up process of 4 bits is performed to each of: the R_(C) data, theG_(C) data, and the B_(C) data; and the R_(D) data, the G_(D) data, andthe B_(D) data. In addition, subtraction of the error data α isperformed, thereby image data of the pixels C and D (that is, thegradation values of the R sub-pixels, the G sub-pixels, and the Bsub-pixels) are extracted. In the above-described manner, thedecompression of the gradation values of the R sub-pixels, G sub-pixels,and B sub-pixels of the pixels C and D is completed.

Comparing image data of pixels A to D in rightmost tables of FIG. 8Bwith image data of pixels A to D in a leftmost table of FIG. 8A, it canbe understood that the original image data of pixels A to D are almostextracted by the above-mentioned decompression method.

As a modified example of the compression method and the decompressionmethod of FIGS. 8A and 8B, while 3 bits are provided to the formrecognition data, the number of combinations of two pixels having a highcorrelation of image data is six, and regarding a certain combination ofthe pixels, the number of bits provided to its representative value canbe accordingly increased. For example, the form recognition data isdefined as follows (x is any value of “0” and “1”)

combination of pixels A and B is 00×,

combination of pixels A and C is 010,

combination of pixels A and D is 011,

combination of pixels B and C is 100,

combination of pixels B and D is 101, and

-   -   combination of pixels C and D is 11x.

In the instance, when two pixels having a high correlation of image dataare the pixels A and B and when two pixels having a high correlation ofimage data are the pixels C and D, the number of bits provided to theform recognition data is set to be 2 bits, and additionally the numberof bits provided to any one of the R representative value, the Grepresentative value, and the B representative value can be increased by1 bit.

FIG. 9B is a view showing a format of the (2+1×2) compression data of acase where: two pixels having a high correlation of image data are thepixels A and B or the pixels C and D; and the number of bits provided tothe G representative value is increased by 1 bit. In the format of FIG.9B, 2 bits are provided to the form recognition data, and 6 bits or 7bits are provided to the G representative value depending on themagnitude relation between the threshold value β and the difference|G_(A)−G_(B)| of the gradation values. By increasing the number of bitsprovided to the G representative value, information amount is increased,thereby a compression distortion can be reduced. In this instance, around-up process of 1 bit or 2 bits is performed on the G representativevalue in the decompression process. The number of bits of the round-upprocess is determined depending on the magnitude relation between thethreshold value β and the difference |G_(A)−G_(B)| of the gradationvalues.

3-3. (2×2) Pixel Compression

FIG. 10A is a conceptual view to explain the (2×2) pixel compression,and FIG. 11A is a conceptual view showing a format of the (2×2) pixelcompression. As described above, the (2×2) pixel compression is acompression method used when there is a high correlation between imagedata of two pixels and there is a high correlation between image data ofother two pixels. As shown in FIG. 11A, in the present embodiment, the(2×2) compression data is 48-bit data, and includes the compression typerecognition bit, the form recognition data, a R representative value #1,a G representative value #1, a B representative value #1, a Rrepresentative value #2, a G representative value #2, a B representativevalue #2, the large-small recognition data, and the β comparison resultdata.

The compression type recognition bit is data that indicates a type of acompression method used for a compression, and 3 bits are allocated tothe compression type recognition bit in the (2×2) compression data. Inthe present embodiment, a value of the compression type recognition bitof the (2×2) compression data is “110”.

The form recognition data is 2-bit data that indicates which one ofcorrelations between image data of two pixels of the pixels A to D ishigh. When the (2×2) pixel compression is employed, a correlation ofimage data between two pixels of the pixels A to D is high and acorrelation of image data of remaining two pixels with the former twopixels is high. Accordingly, there are three combinations of two pixelshaving a high correlation of image data as follows;

the correlation of the pixels A and B is high and the correlation of thepixels C and D is high,

the correlation of the pixels A and C is high and the correlation of thepixels B and D is high, and

the correlation of the pixels A and D is high and the correlation of thepixels B and C is high.

The form recognition data indicates any one of these three combinationsby 2 bits.

The R representative value #1, G representative value #1, and Brepresentative value #1 are values representing gradation values of theR sub-pixel, G sub-pixel, and B sub-pixel of one of two pairs of the twopixels, respectively, and the R representative value #2, Grepresentative value #2, and B representative value #2 are valuesrepresenting gradation values of the R sub-pixel, G sub-pixel, and Bsub-pixel of the other of the two pairs, respectively. In the example ofFIG. 11A, the R representative value #1, the G representative value #1,the B representative value #1, the R representative value #2, and the Brepresentative value #2 are 5-bit data or 6-bit data, and the Grepresentative value #2 is 6-bit data or 7-bit data.

The β comparison data is data that indicates whether or not each of adifference between gradation values of the R sub-pixels of two pixelshaving a high correlation, a difference between image data of the Gsub-pixels of the two pixels having the high correlation, and adifference between image data of the B sub-pixels of the two pixels isgreater than the predetermined threshold value β. In the presentembodiment, the β comparison data is 6-bit data where 3 bits areallocated to each of two pairs of two pixels. Meanwhile, the large-smallrecognition data is data that indicates: which one of the gradationvalues of the R sub-pixels of the two pixels having the high correlationis larger; and which one of the gradation values of the G sub-pixels ofthe two pixels is larger. The large-small recognition data correspondingto the R sub-pixel is generated only when the difference betweengradation values of R sub-pixels of two pixels having a high correlationis larger than the threshold value β, the large-small recognition datacorresponding to the G sub-pixel is generated only when the differencebetween gradation values of G sub-pixels of two pixels having the highcorrelation is larger than the threshold value β, and the large-smallrecognition data corresponding to the B sub-pixel is generated only whenthe difference between gradation values of B sub-pixels of two pixelshaving the high correlation is larger than the threshold value β.Accordingly, the large-small recognition data is 0 to 6-bit data.

Referring to FIG. 10A, the (2×2) pixel compression will be explainedbelow. FIG. 10A describes generation of the (2×2) compressed data in acase where: a correlation between image data of the pixels A and B ishigh; and a correlation between image data of the pixels C and D ishigh. A person skilled in the art will easily understand that the (2×2)compressed data can be generated in the same manner also in other cases.

First of all, regarding each of the R sub-pixel, the G sub-pixel, andthe B sub-pixel, an average value of gradation values is calculated. Theaverage values Rave1, Gave1, and Bave1 of the gradation values of theRsub-pixels, the G sub-pixels, and the B sub-pixels of the pixels A andB, and the average values Rave2, Gave2, and Bave2 of the gradationvalues of the R sub-pixels, the G sub-pixels, and the B sub-pixels ofthe pixels C and D are calculated by following expressions,

Rave1=(R _(A) +R _(B)+1)/2,

Gave1=(G _(A) +G _(B)+1)/2,

Bave1=(B _(A) +B _(B)+1)/2,

Rave2=(R _(C) +R _(D)+1)/2,

Gave2=(G _(C) +G _(D)+1)/2,

Bave2=(B _(C) +B _(D)+1)/2.

In addition, comparison as to whether or not each of a difference|R_(A)−R_(B)| of gradation values of R sub-pixels of the pixels A and B,a difference |G_(A)−G_(B)| of gradation values of G sub-pixels, and adifference |B_(A)-B_(B)| of gradation values of B sub-pixels is largerthan the predetermined threshold value β. In the same manner, comparisonas to whether or not each of a difference |R_(C)−R_(D)| of gradationvalues of R sub-pixels of the pixels C and D, a difference |G_(C)−G_(D)|of gradation values of G sub-pixels, and a difference |B_(C)−B_(D)| ofgradation values of B sub-pixels is larger than the predeterminedthreshold value β. These comparison results are described in the (2×2)compressed data as the β comparison data.

Moreover, the large-small recognition data related to each of acombination of the pixels A and B and to a combination of the pixels Cand D are created.

Specifically, when the difference |R_(A)−R_(B)| of gradation values of Rsub-pixels of the pixels A and B is larger than the threshold value β,it is described to the large-small recognition data which one ofgradation values of the R sub-pixels of the pixels A and B is larger.When the difference |R_(A)−R_(B)| of gradation values of R sub-pixels ofthe pixels A and B is equal to or less than the threshold value β, themagnitude relation of the gradation values of the R sub-pixels of thepixels A and B is not described in the large-small recognition data. Inthe same manner, when the difference |G_(A)−G_(B)| of gradation valuesof G sub-pixels of the pixels A and B is larger than the threshold valueβ, it is described to the large-small recognition data which one ofgradation values of the G sub-pixels of the pixels A and B is larger.When the difference |G_(A)−G_(B)| of gradation values of G sub-pixels ofthe pixels A and B is equal to or less than the threshold value β, themagnitude relation of the gradation values of the G sub-pixels of thepixels A and B is not described in the large-small recognition data. Inaddition, when the difference |B_(A)−B_(B)| of gradation values of Bsub-pixels of the pixels A and B is larger than the threshold value β,it is described to the large-small recognition data which one ofgradation values of the B sub-pixels of the pixels A and B is larger.When the difference |B_(A)−B_(B)| of gradation values of B sub-pixels ofthe pixels A and B is equal to or less than the threshold value β, themagnitude relation of the gradation values of the B sub-pixels of thepixels A and B is not described in the large-small recognition data.

Similarly, when the difference |R_(C)−R_(D)| of gradation values of Rsub-pixels of the pixels C and D is larger than the threshold value β,it is described to the large-small recognition data which one ofgradation values of the R sub-pixels of the pixels C and D is larger.When the difference |R_(C)−R_(D)| of gradation values of R sub-pixels ofthe pixels C and D is equal to or less than the threshold value β, themagnitude relation of the gradation values of the R sub-pixels of thepixels C and D is not described in the large-small recognition data. Inthe same manner, when the difference |G_(C)−G_(D)| of gradation valuesof G sub-pixels of the pixels C and D is larger than the threshold valueβ, it is described to the large-small recognition data which one ofgradation values of the G sub-pixels of the pixels C and D is larger.When the difference |G_(C)−G_(D)| of gradation values of G sub-pixels ofthe pixels C and D is equal to or less than the threshold value β, themagnitude relation of the gradation values of the G sub-pixels of thepixels C and D is not described in the large-small recognition data. Inaddition, when the difference |B_(C)−B_(D)| of gradation values of Bsub-pixels of the pixels C and D is larger than the threshold value β,it is described to the large-small recognition data which one ofgradation values of the B sub-pixels of the pixels C and D is larger.When the difference |B_(C)−B_(D)| of gradation values of B sub-pixels ofthe pixels C and D is equal to or less than the threshold value β, themagnitude relation of the gradation values of the B sub-pixels of thepixels C and D is not described in the large-small recognition data.

In the example of FIG. 10A, the gradation values of the R sub-pixels ofthe pixels A and B are 50 and 59, respectively, and the threshold valueβ is 4. In this instance, since the difference |R_(A)−R_(B)| of thegradation values is larger than the threshold value β, the result isdescribed in the β comparison data, and it is described to thelarge-small recognition data that the gradation value of the R sub-pixelof the pixel B is larger than the gradation value of the R sub-pixel ofthe pixel A. Meanwhile, the gradation values of the G sub-pixels of thepixels A and B are 2 and 1, respectively. Since the difference|G_(A)−G_(B)| of the gradation values is equal to or less the thresholdvalue β, the result is described in the β comparison data. The magnituderelation of the gradation values of the G sub-pixels of the pixels A andB is not described in the large-small recognition data. In addition, thegradation values of the B sub-pixels of the pixels A and B are 30 and39, respectively. In this instance, since the difference |B_(A)−B_(B)|of the gradation values is larger than the threshold value β, the resultis described in the β comparison data, and it is described to thelarge-small recognition data that the gradation value of the B sub-pixelof the pixel B is larger than the gradation value of the B sub-pixel ofthe pixel A.

In addition, both of the gradation values of the R sub-pixels of thepixels C and D are 100. In this instance, since the difference|R_(C)−R_(D)| of the gradation values is equal to of less than thethreshold value β, the result is described in the β comparison data. Themagnitude relation of the gradation values of the G sub-pixels of thepixels A and B is not described in the large-small recognition data.Moreover, the gradation values of the G sub-pixels of the Pixels C and Dare 80 and 85, respectively. In this instance, since the difference|G_(A)−G_(B)| of the gradation values is larger than the threshold valueβ, the result is described in the β comparison data, and it is describedto the large-small recognition data that the gradation value of the Gsub-pixel of the pixel D is larger than the gradation value of the Gsub-pixel of the pixel C. Furthermore, the gradation values of the Bsub-pixels of the pixels C and D are 8 and 2, respectively. In thisinstance, since the difference |B_(C)−B_(D)| of the gradation values islarger than the threshold value β, the result is described in the βcomparison data, and it is described to the large-small recognition datathat the gradation value of the B sub-pixel of the pixel C is largerthan the gradation value of the B sub-pixel of the pixel D.

Moreover, the error data α is added to: the average values Rave1, Gave1,and Bave1 of the gradation values of the R sub-pixel, the G sub-pixel,and B sub-pixel of the pixels A and B; and the average values Rave2,Gave2, and Bave2 of the gradation values of the R sub-pixel, the Gsub-pixel, and B sub-pixel of the pixels C and D. In the presentembodiment, the error data α is determined on the basis of coordinatesof the two pixels of each combination by using a basic matrix that isthe Bayer-Matrix. The calculation of the error data a will be describedbelow. Supposing that the error data a determined for the pixels A and Bis “0”, the present embodiment will be explained below.

Furthermore, a rounding process and a bit round-down process areperformed, thereby the R representative value #1, the G representativevalue #1, the B representative value #1, the R representative value #2,the G representative value #2, and the B representative value #2 arecalculated. At first, for explanation regarding the pixels A and B, avalue added in the rounding process and the number of bits rounded downin the bit round-down process are determined to be 2 bits or 3 bitsdepending on the magnitude relation of the threshold value β with thedifferences |R_(A)−R_(B)|, |G_(A)−G_(B)|, and |B_(A)-B_(B)| of thegradation values. As for the R sub-pixel, when the difference|R_(A)−R_(B)| of the gradation values of R sub-pixels is larger than thethreshold value β, a process to round lower 3 bits down after adding avalue 4 to the average value Rave1 of the gradation values of the Rsub-pixels is performed, thereby the R representative value #1 iscalculated. When the difference |R_(A)−R_(B)| is not larger than thethreshold value β, a process to round lower 2 bits down after adding avalue 2 to the average value Rave1 is performed, thereby the Rrepresentative value #1 is calculated. As a result, the R representativevalue #1 has 5 bits or 6 bits. This is much the same for the G sub-pixeland the B sub-pixel. When the difference |G_(A)−G_(B)| of the gradationvalues is larger than the threshold value β, a process to round lower 3bits down after adding a value 4 to the average value Gave1 of thegradation values of the G sub-pixels is performed, thereby the Grepresentative value #1 is calculated. When the difference |G_(A)−G_(B)|is not larger than the threshold value β, a process to round lower 2bits down after adding a value 2 to the average value Gave1 isperformed, thereby the G representative value #1 is calculated. Inaddition, when the difference |B_(A)−B_(B)| of the gradation values islarger than the threshold value β, a process to round lower 3 bits downafter adding a value 4 to the average value Bave1 of the gradationvalues of the B sub-pixels is performed, thereby the B representativevalue #1 is calculated. When the difference |B_(A)−B_(B)| is not largerthan the threshold value β, a process to round lower 2 bits down afteradding a value 2 to the average value Bave1 is performed, thereby the Brepresentative value #1 is calculated.

In the example of FIG. 10A, as for the average value Rave1 of the Rsub-pixels of the pixels A and B, a process to round lower 3 bits downafter adding a value 4 is performed, thereby the R representative value#1 is calculated. In addition, as for the average value Gave1 of the Gsub-pixels of the pixels A and B, a process to round lower 2 bits downafter adding a value 2 is performed, thereby the G representative value#1 is calculated. Moreover, as for the average value Bave1 of the Bsub-pixels of the pixels A and B, a process to round lower 3 bits downafter adding a value 4 is performed, thereby the B representative value#1 is calculated.

The same process is performed to the combination of the pixels C and D,thereby the R representative value #2, the G representative value #2,and the B representative value #2 are calculated. However, as for the Gsub-pixels of the pixels C and D, a value added in the rounding processand the number of bits rounded down in the bit round-down process are 1bit or 2 bits. When the difference |G_(C)−G_(D)| of the gradation valuesis larger than the threshold value β, a process to round lower 2 bitsdown after adding a value 2 to the average value Gave2 of the gradationvalues of the G sub-pixels is performed, thereby the G representativevalue #2 is calculated. When the difference |G_(C)−G_(D)| is not largerthan the threshold value β, a process to round lower 1 bits down afteradding a value 1 to the average value Gave2 is performed, thereby the Grepresentative value #2 is calculated.

In the example of FIG. 10A, as for the average value Rave2 of the Rsub-pixels of the pixels C and D, a process to round lower 2 bits downafter adding a value 2 is performed, thereby the R representative value#2 is calculated. In addition, as for the average value Gave2 of the Gsub-pixels of the pixels C and D, a process to round lower 3 bits downafter adding a value 4 is performed, thereby the G representative value#2 is calculated. Moreover, as for the B sub-pixels of the pixels C andD, a process to round lower 3 bits down after adding a value 4 to theaverage value Bave 2 of the gradation values of the B sub-pixels isperformed, thereby the B representative value #2 is calculated.

As described above, the compression process by the (2×2) pixelcompression is completed.

Meanwhile, FIG. 10B is a view showing a decompression method of thecompressed image data compressed in the (2×2) pixel compression. FIG.10B describes decompression of the (2×2) compressed data in a casewhere: a correlation between image data of the pixels A and B is high;and a correlation between image data of the pixels C and D is high. Aperson skilled in the art will easily understand that the (2×2)compressed data can be decompressed in the same manner also in othercases.

First of all, a bit round-up process is performed to the Rrepresentative value #1, the G representative value #1, and the Brepresentative value #1. The number of bits of the bit round-up processis determined depending on the magnitude relation of the threshold valueβ with the differences |R_(A)−R_(B)|, |G_(A)−G_(B)|, and |B_(A)−B_(B)|of the gradation values, the magnitude relation being described in the βcomparison data. When the difference |R_(A)−R_(B) of gradation values ofR sub-pixels of the pixels A and B is larger than the threshold value β,the bit round-up process of 3 bits is performed on the R representativevalue #1, and when the difference |R_(A)−R_(B) is not larger than thethreshold value β, the bit round-up process of 2 bits is performed. Inthe same manner, when the difference |G_(A)−G_(B)| between gradationvalues of G sub-pixels of the pixels A and B is larger than thethreshold value β, the bit round-up process of 3 bits is performed onthe G representative value #1, and when the difference |G_(A)−G_(B)| isnot larger than the threshold value β, the bit round-up process of 2bits is performed. In addition, when the difference |B_(A)−B_(B)|between gradation values of B sub-pixels of the pixels A and B is largerthan the threshold value β, the bit round-up process of 3 bits isperformed on the B representative value #1, and when the difference|B_(A)-B_(B)| is not larger than the threshold value β, the bit round-upprocess of 2 bits is performed. In the example of FIG. 10B, regardingthe R representative value #1, the process to round 3 bits up isperformed, regarding the G representative value #1, the process to round2 bits up is performed, and regarding the B representative value #1, theprocess to round 3 bits up is performed.

The same bit round-up process is performed to the R representative value#2, the G representative value #2, and the B representative value #2.However, the number of bits of the bit round-up process for the Grepresentative value #2 is selected from 1 bit or 2 bits. When thedifference |G_(C)−G_(D)| between gradation values of G sub-pixels of thepixels C and D is larger than the threshold value β, the bit round-upprocess of 2 bits is performed on the G representative value #2, andwhen the difference |G_(C)−G_(D)| is not larger than the threshold valueβ, the bit round-up process of 1 bit is performed. In the example ofFIG. 10B, regarding the R representative value #2, the process to round2 bits up is performed, regarding the G representative value #2, theprocess to round 2 bits up is performed, and regarding the Brepresentative value #2, the process to round 3 bits up is performed.

In addition, after subtracting the error data a from each of the Rrepresentative value #1, the G representative value #1, the Brepresentative value #1, the R representative value #2, the Grepresentative value #2, and the B representative value #2, a process toextract: the gradation values of the R sub-pixel, the G sub-pixel, andthe B sub-pixel of the pixels A and B; and the gradation values of the Rsub-pixel, the G sub-pixel, and the B sub-pixel of the pixels C and Dfrom these representative values is performed.

In the extraction of the gradation values, the β comparison data and thelarge-small recognition data are used. When it is described in the βcomparison data that the difference |R_(A)−R_(B)| of the gradationvalues of the R sub-pixels of the pixels A and B are larger than thethreshold value β, a value obtained by adding a constant value 5 to theR representative value #1 is extracted as the gradation value of the Rsub-pixel of larger one of the pixels A and B described in thelarge-small recognition data, and a value obtained by subtracting theconstant value 5 from the R representative value #1 is extracted as thegradation value of the R sub-pixel of the smaller one described in thelarge-small recognition data. When the difference |R_(A)−R_(B)| of thegradation values of the R sub-pixels of the pixels A and B are smallerthan the threshold value β, the gradation values of the R sub-pixels ofthe pixels A and B is extracted as being equal to the R representativevalue #1. In the same manner, the gradation values of the G sub-pixelsand the B sub-pixels of the pixels A and B and the gradation values ofthe R sub-pixels, the G sub-pixels, and the B sub-pixels of the pixels Cand D are extracted in the same procedure.

In the example of FIG. 10B, the gradation value of the R sub-pixel ofthe pixel A is extracted as a value obtained by subtracting only a value5 from the R representative value #1, and the gradation value of the Rsub-pixel of the pixel B is extracted as a value obtained by adding avalue 5 to the R representative value #1. In addition, the gradationvalues of the G sub-pixels of the pixels A and B is extracted as beingequal to the G representative value #1. Moreover, the gradation value ofthe B sub-pixel of the pixel A is extracted as a value obtained bysubtracting only a value 5 from the B representative value #1, and thegradation value of the B sub-pixel of the pixel B is extracted as avalue obtained by adding a value 5 to the B representative value #1.Meanwhile, the gradation values of the R sub-pixels of the pixels C andD is extracted as being equal to the R representative value #2.Furthermore, the gradation value of the G sub-pixel of the pixel C isextracted as a value obtained by subtracting only a value 5 from the Grepresentative value #2, and the gradation value of the G sub-pixel ofthe pixel D is extracted as a value obtained by adding a value 5 to theG representative value #2. Additionally, the gradation value of the Bsub-pixel of the pixel C is extracted as a value obtained by adding avalue 5 to the B representative value #2, and the gradation value of theB sub-pixel of the pixel D is extracted as a value obtained bysubtracting a value 5 from the B representative value #2.

As described above, the extraction of the gradation values of the Rsub-pixels, the G sub-pixels, and the B sub-pixels of the pixels A to Dis completed. Comparing image data of pixels A to D in a rightmost tableof FIG. 10B with image data of pixels A to D in leftmost tables of FIG.10A, it can be understood that original image data of pixels A to D arealmost extracted by the above-mentioned decompression method.

As a modified example of the compression method and decompression methodof FIGS. 10A and 10B, while 2 bits are provided to the form recognitiondata, the number of combinations of two pixels having a high correlationof image data is three, and regarding a certain combination of thepixels, the number of bits provided to its representative value can beaccordingly increased. For example, the form recognition data is definedas follows (x is any value of “0” and “1”);

a correlation between pixels A and B is high and a correlation betweenpixels C and D is high: 0x,

a correlation between pixels A and C is high and a correlation betweenpixels B and D is high: 10,

a correlation between pixels A and D is high and a correlation betweenpixels B and C is high: 11.

In the instance, only when the correlation between image data of thepixels A and B is high and the correlation between image data of thepixels C and D is high, the number of bits provided to the formrecognition data is set to be 1 bits, and additionally the number ofbits provided to any one of the R representative value #1, the Grepresentative value #1, the B representative value #1, the Rrepresentative value #2, and the B representative value #2 can beincreased by 1 bit. To improve symmetry of data of: combination of thepixels A and B; and combination of the pixels C and D, it is favorableto increase the number of bits provided to the G representative value #1by 1 bit.

FIG. 11B is a view showing a format of the (2×2) compression data of acase where the number of bits provided to the G representative value #1is increased by 1 bit when correlation between image data of the pixelsA and B is high and correlation between image data of the pixels C and Dis high. In the format of FIG. 11B, 1 bit is provided to the formrecognition data, and 6 bits or 7 bits are provided to the Grepresentative value #1 depending on the magnitude relation between thedifference |G_(A)−G_(B)| of the gradation values and the threshold valueβ. By increasing the number of bits provided to the G representativevalue #1, information amount is increased, thereby a compressiondistortion can be reduced. In this instance, a round-up process of 1 bitor 2 bits is performed to the G representative value #1 in thedecompression process. The number of bits of the round-up process isdetermined depending on the magnitude relation between the difference|G_(A)−G_(B)| of the gradation values and the threshold value β.

3-4. (4×1) Pixel Compression

FIG. 12A is a conceptual view to explain the (4×1) pixel compression,and FIG. 13 is a conceptual view showing a format of data of the (4×1)pixel compression. As described above, the (4×1) pixel compression is acompression method used when there is a high correlation of image dataof four pixels of a target block. As shown in FIG. 13, in the presentembodiment, the (4×1) compression data is 48-bit data, and includes: acompression type recognition bit; and the following seven data, Ymin,Ydist0 to Ydist2, address data, Cb′, and Cr′.

The compression type recognition bit is data that indicates a type ofcompression method used for a compression, and 4 bits are allocated tothe compression type recognition bit in the (4×1) compressed data. Inthe present embodiment, a value of the compression type recognition bitof the (4×1) compressed data is “1110”.

The Ymin, Ydist0 to Ydist2, address data, Cb′, and Cr′ are data obtainedby: converting image data of four pixels of a target block from RGB datainto YUV data; and further performing a compression process on the YUVdata. Here, the Ymin and Ydist0 to Ydist2 are data obtained frombrightness data among the YUV data of four pixels of the target block,and the Cb′ and Cr′ are data obtained from color-difference data. TheYmin, Ydist0 to Ydist2, Cb′, and Cr′ are representative values of imagedata of four pixels of the target block. In the present embodiment, 10bits are allocated to the data Ymin, 4 bits are allocated to each of theYdist0 to Ydist2, 2 bits are allocated to the address data, and 10 bitsare allocated to each of the Cb′ and Cr′. Referring to FIG. 12A, the(4×1) pixel compression will be explained below.

At first, regarding each of the pixels A to D, the brightness data Y andthe color-difference data Cr and Cb are calculated by the followingmatrix operation;

$\begin{matrix}{{\begin{bmatrix}Y_{k} \\{Cr}_{k} \\{Cb}_{k}\end{bmatrix} = {\begin{bmatrix}1 & 2 & 1 \\0 & {- 1} & 1 \\1 & {- 1} & 0\end{bmatrix}\begin{bmatrix}R_{k} \\G_{k} \\B_{k}\end{bmatrix}}},} & \left\lbrack {{Expression}\mspace{14mu} 1} \right\rbrack\end{matrix}$

Here, the Y_(k) is brightness data of a pixel k, the Cr_(k) and Cb_(k)are color-difference data of the pixel k. In addition, as describedabove, R_(k), G_(k), and B_(k) are the gradation values of the Rsub-pixel, the G sub-pixel, and the B sub-pixel, respectively.

In addition, the Ymin, Ydist0 to Ydist2, address data, Cb′, and Cr′ arecreated from the brightness data Y_(k) of the pixels A to D and thecolor-difference data Cr_(k) and Cb_(k).

The Ymin is defined as a minimum data (minimum brightness data) of thebrightness data Y_(A) to Y_(D). In addition, the Ydist0 to Ydist2 aregenerated by performing a round-down process of 2 bits on differencesbetween the remaining brightness data and the minimum brightness dataYmin. The address data is generated as data for indicating which one ofthe brightness data of the pixels A to D is the minimum. In the exampleof FIG. 12A, the Ymin, and the Ydist0 to Ydist2 are calculated by thefollowing expressions;

Ymin=Y_(D)=4,

Ydist0=(Y _(A) −Ymin)>>2=(48−4)>>2=11,

Ydist1=(Y _(B) −Ymin)>>2=(28−4)>>2=6,

Ydist2=(Y _(C) −Ymin)>>2=(16−4)>>2=3,

Where the “>>2” is an operator representing a round-down process of 2bits. It is described to the address data that the brightness data Y_(D)is the minimum.

Moreover, the Cr′ is generated by performing a round-down process of 1bit on a summation of Cr_(A) to Cr_(D), and the Cb′ is similarlygenerated by performing the round-down process of 1 bit on a summationof Cb_(A) to Cb_(D). In the example of FIG. 12A, the Cr′ and Cb′ arecalculated by the following expressions;

Cr^(′) = (Cr_(A) + Cr_(B) + Cr_(C) + Cr_(D))>> 1    = (−2 − 1 + 1 − 1)>> 1 = −1, andCb^(′) = (Cb_(A) + Cb_(B) + Cb_(C) + Cb_(D))>> 1    = (2 + 1 − 1 + 1)>> 1 = 1,

Where the “>>1” is an operator representing a round-down process of 1bit. In the above-described manner, the generation of the (4×1)compressed data is completed.

Meanwhile, FIG. 12B is a view showing a decompression method ofcompressed image data compressed by the (4×1) pixel compression. In thedecompression of compressed image data compressed by the (4×1) pixelcompression, the brightness data of each of the pixels A to D arefirstly extracted from the Ymin, and the Ydist0 to Ydist2. The extractedbrightness data of the pixels A to D are described as Y_(A)′ to Y_(D)′below. More specifically, a value of the minimum brightness data Ymin isused as the brightness data of pixel indicated as the minimum data bythe address data. In addition, by adding the Ydist0 to Ydist2 to theminimum brightness data Ymin after performing a round-up process of 2bits on them, the brightness data of other pixels are extracted. In thepresent embodiment, the brightness data Y_(A)′ to Y_(D)′ are extractedby the following expressions;

Y _(A) ′=Ydist0×4+Ymin=44+4=48,

Y _(B) ′=Ydist1×4+Ymin=24+4=28,

Y _(C) ′=Ydist2×4+Ymin=12+4=16, and

Y_(D)′=Ymin=4.

Moreover, the gradation values of the R, G, B sub-pixels of the pixels Ato D are extracted from the brightness data Y_(A)′ to Y_(D)′ and thecolor-difference data Cr′ and Cb′ by the following matrix operation;

$\begin{matrix}{{{\begin{bmatrix}R_{k} \\G_{k} \\B_{k}\end{bmatrix} = {\begin{bmatrix}1 & {- 1} & 3 \\1 & {- 1} & {- 1} \\1 & 3 & {- 1}\end{bmatrix}\begin{bmatrix}Y_{k}^{\prime} \\{Cr}^{\prime} \\{Cb}^{\prime}\end{bmatrix}}}\operatorname{>>}2},} & \left\lbrack {{Expression}\mspace{14mu} 2} \right\rbrack\end{matrix}$

Where the “1>>2” is the operator indicating the round-down process of 2bits. As understood from the above-mentioned expression, in theextraction of the gradation values of the R, G, and B sub-pixels of thepixels A to D, the color-difference data Cr′ and Cb′ are commonly used.

In the above-described manner, the decompression of the gradation valuesof the R sub-pixels, G sub-pixels, and B sub-pixels of the pixels A to Dis completed. Comparing image data of pixels A to D in a rightmost tableof FIG. 12B with image data of pixels A to D in a leftmost table of FIG.12A, it can be understood that the original image data of pixels A to Dare almost extracted by the above-mentioned decompression method.

3-5. Calculation of Error Data α

Calculation of the error data a used in the (1×4) pixel compression, the(2+1×2) pixel compression, and the (2×2) pixel compression will beexplained below.

The error data a used for the bit plane reduction process performed toeach pixels, the bit plane reduction process being performed in the(1×4) pixel compression and the (2+1×2) pixel compression, is calculatedfrom the basic matrix shown in FIG. 14 and coordinates of each pixels.Here, the basic matrix is a matrix where a relation between: lower 2bits, X1 and X0 of an X coordinate of pixel and lower 2 bits, Y1 and Y0of a Y coordinate; and a basic value Q of the error data α. The basicvalue Q is a value used as a seed for calculation of the error data α.

Specifically, the basic value Q is firstly extracted from among matrixelements of the basic matrix on the basis of lower 2 bits, X1 and X0 ofan X coordinate and lower 2 bits, Y1 and Y0 of a Y coordinate of atarget pixel. For example, when a target of the bit plane reductionprocess is the pixel A and the lower 2 bits of coordinates of the pixelA is “00”, “15” is extracted as the basic value Q.

In addition, the following operation is performed to the basic value Qbased on the number of bits of the bit round-down process subsequentlyperformed in the bit plane reduction process, thereby the error data αis calculated;

α=Q×2:(the number of bits in the bit round-down process is 5),

α=Q:(the number of bits in the bit round-down process is 4), and

α=Q/2:(the number of bits in the bit round-down process is 3).

Meanwhile, the error data a used for a calculation process ofrepresentative values of image data of two pixels having a highcorrelation in the (2+1×2) pixel compression and the (2×2) pixelcompression is calculated from: the basic matrix shown in FIG. 14; andlower 2 bits X1 and Y1 of the X coordinate and the Y coordinate of thetarget two pixels. Specifically, any one of the pixels if the targetblock is determined as a pixel used to extract the basic value Q. Thepixel used to extract the basic value Q is described as a Q extractionpixel below. A relation between: a combination of target two pixels; andthe Q extraction pixel is as follows.

In a case where the target two pixels are Pixels A and B, the Qextraction pixel is the pixel A.

In a case where the target two pixels are Pixels A and C, the Qextraction pixel is the pixel A.

In a case where the target two pixels are Pixels A and D, the Qextraction pixel is the pixel A.

In a case where the target two pixels are Pixels B and C, the Qextraction pixel is the pixel B.

In a case where the target two pixels are Pixels B and D, the Qextraction pixel is the pixel B.

In a case where the target two pixels are Pixels C and D, the Qextraction pixel is the pixel B.

In addition, the basic value Q corresponding to the Q extraction pixelis extracted from the basic matrix based on X1 and Y1 at lower 2nd bitsof the X coordinate and Y coordinate of the target two pixels. Forexample, when the target two pixels are the pixels A and B, the Qextraction pixel is the pixel A. In this instance, the basic value Q tobe used is finally determined based on the X1 and Y1 from among fourbasic values Q related to the pixel A of the Q extraction pixel in thebasic matrix as follows;

Q=15 (X1=Y1=“0”),

Q=01 (X1=“1”, Y1=“0”)

Q=07 (X1=“0”, Y1=“1”), and

Q=13 (X1=Y1=“11”).

Moreover, the following operations are performed on the basic value Qbased on the number of bits of the bit round-down process subsequentlyperformed in the calculation of the representative value, thereby theerror data a used for a calculation process of a representative value ofimage data of two pixels having a high correlation is calculated;

α=Q/2: (the number of bits of the bit round-down process is 3),

α=Q/4: (the number of bits of the bit round-down process is 2), and

α=Q/8: (the number of bits of the bit round-down process is 1).

For example, when the target two pixels are the pixels A and B,X1=Y1=“1”, and the number of bits of the bit round-down process is 3,the error data α is determined by a following expression;

Q=13, and

α=13/2=6.

Additionally, the calculation method of the error data α is not limitedto the above-mentioned method. For example, another matrix that is theBayer-Matrix may be used as the basic matrix.

3-6. Compression Type Recognition Bit

One of matters to be noted in the compression method explained above isallocation of the number of bits of the compression type recognition bitin each compressed image data. In the present embodiment, the number ofbits of the compressed image data is fixed to 48 bits, however, thecompression type recognition bit is variable from 1 to 4 bits.Specifically, in the present embodiment, the compression typerecognition bits of the (1×4) pixel compression, the (2+1×2) pixelcompression, the (2×2) pixel compression, and the (4×1) pixelcompression are as follows;

(1×4) pixel compression: “0” (1 bit),

(2+1×2) pixel compression: “10” (2 bits),

(2×2) pixel compression: “110” (3 bits), and

(4×1) pixel compression: “1110” (4 bits).

It should be noted that the lower a correlation between image data ofpixels of the target block is, the smaller the number of bits allocatedto the compression type recognition bit is, and the higher a correlationbetween image data of pixels of the target block is, the larger thenumber of bits allocated to the compression type recognition bit is.

To fix the number of bits of the compressed image data regardless of thecompression method is effective way to simplify sequences of: writing ofcompressed image data to the image memory 14; and reading the compressedimage data from the image memory 14.

Meanwhile, in order to reduce a compression distortion as a whole, it iseffective that the lower a correlation between image data of pixels ofthe target block is, the smaller the number of bits allocated to thecompression type recognition bit is (that is, the number of bitsallocated to image data is large). In a case where a correlation betweenimage data of pixels of a target block is high, the image data can becompressed with suppressing deterioration of image even when the numberof bits allocated to the image data is small. On the other hand, in acase where a correlation between image data of pixels of a target blockis low, the number of bits allocated to the image data is increased,thereby the compression distortion is reduced.

Second Embodiment

FIG. 15 is a block diagram showing a configuration of a liquid crystaldisplay device according to a second embodiment of the presentinvention. The configuration of the liquid crystal display deviceaccording to the second embodiment is almost the same as theconfiguration of the liquid crystal display device of the firstembodiment. However, the liquid crystal display device in the secondembodiment is configured so as to perform the lossless compression whenimage data of a target block has a specific pattern. This is forenabling an appropriate inspection of the LCD panel 2. In the inspectionof the LCD panel 2, evaluations of the brightness characteristic and thecolor gamut characteristic are carried out in the inspection of the LCDpanel 2. In these evaluations of the brightness characteristic and thecolor gamut characteristic, an image of a specific pattern is displayedon the LCD panel 2. At this time, to appropriately evaluate thebrightness characteristic and the color gamut characteristic, it isrequired to display an image where colors are faithfully reproduced withrespect to inputted image data on the LCD panel 2; if a compressiondistortion exists, the evaluations of the brightness characteristic andthe color gamut characteristic cannot be appropriately carried out.Accordingly, a circuit for carry out the lossless compression is addedto the liquid crystal display device of the second embodiment.

Specifically, a lossless compression portion 36 is added to the imagecompression circuit 13, and an original data extraction portion 46 isadded to the image decompression circuit 15. When image data of pixelsof a target block has a specific form, the lossless compression portion36 compresses the image data in a lossless manner and generates losslesscompressed data. The original data extraction portion 46 decompressesthe lossless compresses data in a decompression method accepting alossless compression performed by the lossless compression portion 36.

FIG. 16 is a flowchart to explain an operation of the liquid crystaldisplay device in the second embodiment. In the second embodiment, it isjudged whether image data of four pixels of a target block correspondsto the specific pattern or not before evaluating a correlation of theimage data of the pixels of the target block, and when the image datacorresponds to the specific pattern, the lossless compression is carriedout. In the present embodiment, a predetermined pattern where the numberof types of data values of image data of a target block is five or lessis selected as a specific pattern to which the loss less compression isperformed.

Specifically, in the second embodiment, the lossless compression iscarried out when image data of four pixels of a target block correspondsto any one of the following four patterns (1) to (4);

(1) Gradation Values of Each Color of Four Pixels are the Same (FIG.17A) Condition (1a):

R_(A)=R_(B)=R_(C)=R_(D),

G_(A)=G_(B)=G_(C)=G_(D), and

B_(A)=B_(B)=B_(C)=B_(D).

In this case, the number of types of data values of the image data ofthe four pixels of the target block is 3.

(2) Gradation Values of R Sub-Pixel, G Sub-Pixel, and B Sub-Pixel arethe Same in Each of Four Pixels (FIG. 17B)

The lossless compression is carried out also in a case where the imagedata of the four pixels of the target block satisfies the followingcondition (2a).

Condition (2a):

R_(A)=G_(A)=B_(A),

R_(B)=G_(B)=B_(B),

R_(C)=G_(C)=B_(C), and

R_(D)=G_(D)=B_(D).

In this case, the number of types of data values of the image data ofthe four pixels of the target block is 4.

(3) Gradation Values of Two Colors of R, G, and B are the Same RegardingFour Pixels of Target Block (FIG. 17c to FIG. 17E)

The lossless compression is carried out also in a case where any one ofthe following three conditions (3a) to (3c) is satisfied.

Condition (3a): G_(A)=G_(B)=G_(C)=G_(D)=B_(A)=B_(B)=B_(C)=B_(D).Condition (3b): B_(A)=B_(B)=B_(C)=B_(D)=R_(A)=R_(B)=R_(C)=R_(D).Condition (3c): R_(A)=R_(B)=R_(C)=R_(D)=G_(A)=G_(B)=G_(C)=G_(D)

In this case, the number of types of data values of the image data ofthe four pixels of the target block is 5.

(4) Gradation Values of One Color of R, G, and B are the Same, andGradation Values of Remaining Two Colors are the Same Regarding FourPixels of Target Block (FIG. 17f to FIG. 17H)

The lossless compression is further carried out also in a case where anyone of the following three conditions (4a) to (4c) is satisfied.

Condition (4a):

G_(A)=G_(B)=G_(C)=G_(D)

R_(A)=B_(A),

R_(B)=B_(B),

R_(C)=B_(C), and

R_(D)=B_(D).

Condition (4b):

B_(A)=B_(B)=B_(c)=B_(D)

R_(A)=G_(A),

R_(B)=G_(B),

R_(C)=G_(C), and

R_(D)=G_(D).

Condition (4c):

R_(A)=R_(B)=R_(C)=R_(D)

G_(A)=B_(A),

G_(B)=B_(B),

G_(C)=B_(C), and

G_(D)=B_(D).

In this case, the number of types of data values of the image data ofthe four pixels of the target block is 5.

Regarding the predetermined pattern, the number of kinds of the imagedata of the N×M pixels is less than (N×M×3/2). The reason is as follows.When the image data of the N×M pixels, the number of the data is (N×M×3)in consideration of R, G and B sub-pixels, is supplied and the data ofeach sub-pixel has k bits, the total number of bits is (N×M×3×k). Ifthis total number of bits is required to be half, (N×M×3×k)/2 bits isrequired to be reduced. The number of bits of compressed data indicatesthe sum of the number of bits of the compressed image data and thenumber of bits of the compression type recognition bit. Therefore, ifthe sum of the number of bits of the compressed image data and thenumber of bits of the compression type recognition bit is equal to orless than (N×M×3×k)/2 bits, the image data can be compressed to be half.In this case, since the number of bits of the compression typerecognition bit is not 0 (zero), the number of bits of the compressedimage data is less than (N×M×3×k)/2 bits. Here, the image data has kbits, and the compressed imaged data can indicate the number of kinds ofthe image data×k bits, thus, the number of kinds of the image data isless than (N×M×3)/2. Therefore, if the image data is data that thenumber of kinds of the image data of the N×M pixels is less than(N×M×3/2), the image data can be compressed to be half.

In the present embodiment, the lossless compression is performed byrearranging data values of image data of pixels of a target block. FIG.18 is a view showing a format of lossless compressed data generated by alossless compression. In the present embodiment, the lossless compresseddata is 48-bit data, and includes a compression type recognition bit,color type data, image data #1 to #5, and padding data.

The compression type recognition bit is data indicating a type of acompression method used for a compression, and four bits are allocatedfor the compression type recognition bit in the lossless compresseddata. In the present embodiment, a value of the compression typerecognition bit of the lossless compression data is “1111”.

The color type data is data indicating which one of the patterns ofFIGS. 17A to 17H corresponds to image data of four pixels of a targetblock. In the present embodiment, since eight specific patters aredefined, the color type data has 3 bits.

The image data #1 to #5 are data obtained by rearranging data values ofthe image data of pixels of the target block. Each of the image data #1to #5 is 8-bit data. As described above, since the number of types ofdata values of the image data of four pixels of the target block is fiveor less, the data value can be stored in all of the image data #1 to #5.

The padding data is data that is added to set the number of bits of thelossless compressed data to be the same as that of compressed image datacompressed by other compression methods. In the present embodiment, thepadding data has 1 bit.

The decompression of the lossless compressed data generated by theabove-mentioned lossless compression is carried out by arranging theimage data #1 to #5 with referring to the color type data. Since it isdescribed to the color type data which one of the patterns of FIGS. 17Ato 17H corresponds to the image data of four pixels of the target data,an original image data of four pixels of the target data can becompletely extracted without generating any compression distortion byreferring to the color type data. By driving the LCD panel 2 based onthe completely extracted image data, the brightness characteristic andthe color gamut characteristic of the LCD panel 2 can be appropriatelyevaluated.

Various types of embodiments of the present invention is described inthe above description, however, the present invention should not beinterpreted within the limitation of the above-described embodiments.For example, the liquid crystal display device having a LCD panel isproposed in the above-mentioned embodiment, however, it is obvious for aperson skilled in the art that the present invention can be applied toother display panels.

Additionally, in the above-mentioned embodiments, the target block isdefined as pixels in 2 rows by 2 columns, however, the target block canbe generally defined as pixels in N rows by M columns (N and M arenatural numbers, and N×M≧4). For example, the target block can bedefined as pixels in 1 row by 4 columns. In this case, the rearrangementof image data using the line memory 12 is not carried out, and the linememory 12 is accordingly not required. Since a size of a hardwareconfiguration can be reduced, it is preferable that the line memory 12is not required.

It is apparent that the present invention is not limited to the aboveembodiment, but may be modified and changed without departing from thescope and spirit of the invention.

Although the present invention has been described above in connectionwith several exemplary embodiments thereof, it would be apparent tothose skilled in the art that those exemplary embodiments are providedsolely for illustrating the present invention, and should not be reliedupon to construe the appended claims in a limiting sense.

1. A display panel driver comprising: a compression circuit configuredto, when receiving image data of N×M (N and M is integer, N×M≧4) pixelsof a target block, generate compressed image data corresponding to saidtarget block by compressing said image data; an image memory configuredto store said compressed image data; a decompression circuit configuredto generate decompressed image data by decompressing said compressedimage data reading from said image memory; and a drive circuitconfigured to drive a display panel in response to said decompressedimage data, wherein said compression circuit selects one of a pluralityof compression methods based on a correlation between said image data ofsaid N×M pixels of said target block, and generates said compressedimage data by using said selected compression method, wherein saidplurality of compression methods includes: a first compression methodwhich calculates a first representative value corresponding to imagedata of said N×M pixels and puts said first representative value in saidcompressed image data, a second compression method which calculates asecond representative value corresponding to image data of n (2≦n≦N×M)pixels of said N×M pixels and puts said second representative value insaid compressed image data, and a third compression method whichcalculates a first bit plane reducing data by performing a bit planereduction process independently on image data of each of said N×M pixelsand puts said first bit plane reducing data in said compressed imagedata.
 2. The display panel driver according to claim 1, wherein thenumber of bits of said compressed image data is constant regardless ofsaid plurality of compression method, wherein said compressed image dataincludes a compression type recognition bit indicating a type of saidselected compression method, wherein the number of bits of saidcompression type recognition bit of said compressed image datacompressed by using said first compression method is equal to or lessthan the number of bits of said compression type recognition bit of saidcompressed image data compressed by using said second compressionmethod, and wherein the number of bits of said compression typerecognition bit of said compressed image data compressed by using saidsecond compression method is equal to or less than the number of bits ofsaid compression type recognition bit of said compressed image datacompressed by using said third compression method.
 3. The display paneldriver according to claim 1, wherein said plurality of compressionmethod further includes: a lossless compression method which losslesslycompresses said image data into said compressed image data, wherein saidcompression circuit, when said image data of said N×M pixels of saidtarget block corresponds to a predetermined pattern, generates saidcompressed image data by using said lossless compression method.
 4. Thedisplay panel driver according to claim 1, wherein said N, said M andsaid n are 2, and wherein said second compression method calculates saidsecond representative value corresponding to image data of 2 pixels of 4pixels of said target block and a third representative valuecorresponding to image data of the other 2 pixels of said 4 pixels ofsaid target block, and puts said second representative value and saidthird representative value in said compressed image data.
 5. The displaypanel driver according to claim 4, wherein said plurality of compressionmethod further includes: a fourth compression method which calculates afourth representative value corresponding to image data of 2 pixels ofsaid 4 pixels of said target block, calculates a second bit planereducing data by performing a bit plane reduction process independentlyon image data of the other 2 pixels of said 4 pixels of said targetblock, and puts said fourth representative value and said second bitplane reducing data in said compressed image data.
 6. The display paneldriver according to claim 5, wherein the number of bits of saidcompressed image data is constant regardless of said plurality ofcompression method, wherein said compressed image data includes acompression type recognition bit indicating a type of said selectedcompression method, wherein the number of bits of said compression typerecognition bit of said compressed image data compressed by using saidfirst compression method is equal to or less than the number of bits ofsaid compression type recognition bit of said compressed image datacompressed by using said second compression method, wherein the numberof bits of said compression type recognition bit of said compressedimage data compressed by using said second compression method is equalto or less than the number of bits of said compression type recognitionbit of said compressed image data compressed by using said fourthcompression method, and wherein the number of bits of said compressiontype recognition bit of said compressed image data compressed by usingsaid fourth compression method is equal to or less than the number ofbits of said compression type recognition bit of said compressed imagedata compressed by using said third compression method.
 7. The displaypanel driver according to claim 6, wherein said compression circuitcalculates a difference between image data of any 2 pixels of said 4pixels of said target block, and (1) selects said third compressionmethod, when said difference between image data of said 2 pixels issmaller than a predetermined value in all combinations of said any 2pixels, (2) selects said fourth compression method, when said thirdcompression method is not selected, and when, with respect to allcombinations of a first set having 2 pixels of said 4 pixels and asecond set having the other 2 pixels of said 4 pixels, a differencebetween image data of said 2 pixels in said first set is not smallerthan a predetermined value and a difference between image data of saidthe other pixels in said second set is not smaller than a predeterminedvalue, (3) selects said second compression method, when said thirdcompression method and said fourth compression method are not selected,and when, with respect to all colors of said 4 pixels, a differencebetween a maximum value of image data of said 4 pixels and minimum valueof image data of said 4 pixels is not smaller than a predeterminedvalue, and (4) selects said first compression method, when said thirdcompression method and said fourth compression method are not selected,and when, with respect to all colors of said 4 pixels, a differencebetween a maximum value of image data of said 4 pixels and minimum valueof image data of said 4 pixels is smaller than a predetermined value. 8.The display panel driver according to claim 1, wherein the number ofbits of said compressed image data corresponding to said target block isa half of the number of bits of said image data before being compressedcorresponding to said target block.
 9. A display device comprising: adisplay panel; and a display panel driver configured to drive saiddisplay panel, wherein said display panel driver includes: a compressioncircuit configured to, when receiving image data of N×M (N and M isinteger, N×M≧4) pixels of a target block, generate compressed image datacorresponding to said target block by compressing said image data, animage memory configured to store said compressed image data, adecompression circuit configured to generate decompressed image data bydecompressing said compressed image data reading from said image memory,and a drive circuit configured to drive a display panel in response tosaid decompressed image data, wherein said compression circuit selectsone of a plurality of compression methods based on a correlation betweensaid image data of said N×M pixels of said target block, and generatessaid compressed image data by using said selected compression method,wherein said plurality of compression methods includes: a firstcompression method which calculates a first representative valuecorresponding to image data of said N×M pixels and puts said firstrepresentative value in said compressed image data, a second compressionmethod which calculates a second representative value corresponding toimage data of n (2≦n≦N×M) pixels of said N×M pixels and puts said secondrepresentative value in said compressed image data, and a thirdcompression method which calculates a first bit plane reducing data byperforming a bit plane reduction process independently on image data ofeach of said N×M pixels and puts said first bit plane reducing data insaid compressed image data.
 10. The display device according to claim 9,wherein the number of bits of said compressed image data is constantregardless of said plurality of compression method, wherein saidcompressed image data includes a compression type recognition bitindicating a type of said selected compression method, wherein thenumber of bits of said compression type recognition bit of saidcompressed image data compressed by using said first compression methodis equal to or less than the number of bits of said compression typerecognition bit of said compressed image data compressed by using saidsecond compression method, and wherein the number of bits of saidcompression type recognition bit of said compressed image datacompressed by using said second compression method is equal to or lessthan the number of bits of said compression type recognition bit of saidcompressed image data compressed by using said third compression method.11. The display device according to claim 9, wherein said plurality ofcompression method further includes: a lossless compression method whichlosslessly compresses said image data into said compressed image data,wherein said compression circuit, when said image data of said N×Mpixels of said target block corresponds to a predetermined pattern,generates said compressed image data by using said lossless compressionmethod.
 12. An image processing circuit comprising: a compressioncircuit configured to, when receiving image data of N×M (N and M isinteger, N×M≧4) pixels of a target block, generate compressed image datacorresponding to said target block by compressing said image data,wherein said compression circuit selects one of a plurality ofcompression methods based on a correlation between said image data ofsaid N×M pixels of said target block, and generates said compressedimage data by using said selected compression method, wherein saidplurality of compression methods includes: a first compression methodwhich calculates a first representative value corresponding to imagedata of said N×M pixels and puts said first representative value in saidcompressed image data, a second compression method which calculates asecond representative value corresponding to image data of n (2≦n≦N×M)pixels of said N×M pixels and puts said second representative value insaid compressed image data, and a third compression method whichcalculates a first bit plane reducing data by performing a bit planereduction process independently on image data of each of said N×M pixelsand puts said first bit plane reducing data in said compressed imagedata.
 13. A display panel driver comprising: a compression circuitconfigured to, when receiving image data of a plurality of pixels of atarget block, generate compressed image data corresponding to saidtarget block by compressing said image data; an image memory configuredto store said compressed image data; a decompression circuit configuredto generate decompressed image data by decompressing said compressedimage data reading from said image memory; and a drive circuitconfigured to drive a display panel in response to said decompressedimage data, wherein said compression circuit selects one of a pluralityof compression methods based on a correlation between said image data ofsaid plurality of pixels of said target block, and generates saidcompressed image data by using said selected compression method, whereinthe number of bits of said compressed image data is constant regardlessof said plurality of compression method, wherein said compressed imagedata includes a compression type recognition bit indicating a type ofsaid selected compression method, and wherein the number of bits of saidcompression type recognition bit of said compressed image data becomeslow, when said correlation between said image data of said plurality ofpixels becomes high.
 14. A display device comprising: a display panel;and a display panel driver configured to drive said display panel,wherein said display panel driver includes: a compression circuitconfigured to, when receiving image data of a plurality of pixels of atarget block, generate compressed image data corresponding to saidtarget block by compressing said image data, an image memory configuredto store said compressed image data, a decompression circuit configuredto generate decompressed image data by decompressing said compressedimage data reading from said image memory, and a drive circuitconfigured to drive a display panel in response to said decompressedimage data, wherein said compression circuit selects one of a pluralityof compression methods based on a correlation between said image data ofsaid plurality of pixels of said target block, and generates saidcompressed image data by using said selected compression method, whereinthe number of bits of said compressed image data is constant regardlessof said plurality of compression method, wherein said compressed imagedata includes a compression type recognition bit indicating a type ofsaid selected compression method, and wherein the number of bits of saidcompression type recognition bit of said compressed image data becomeslow, when said correlation between said image data of said plurality ofpixels becomes high.
 15. An image processing circuit comprising: acompression circuit configured to, when receiving image data of aplurality of pixels of a target block, generate compressed image datacorresponding to said target block by compressing said image data,wherein said compression circuit selects one of a plurality ofcompression methods based on a correlation between said image data ofsaid plurality of pixels of said target block, and generates saidcompressed image data by using said selected compression method, whereinthe number of bits of said compressed image data is constant regardlessof said plurality of compression method, wherein said compressed imagedata includes a compression type recognition bit indicating a type ofsaid selected compression method, and wherein the number of bits of saidcompression type recognition bit of said compressed image data becomeslow, when said correlation between said image data of said plurality ofpixels becomes high.